From 9e53873377ac6e3b0ba5e86e0e184a4603531fed Mon Sep 17 00:00:00 2001
From: sonurdogan <onurdgn14@hotmail.com>
Date: Fri, 17 Nov 2023 13:06:31 +0300
Subject: [PATCH] WhisperForCTC Integration

---
 ...atic_speech_recognition_overview_ASR.ipynb | 607 ++++++++++++++----
 .../classifiers/asr_whisper/__init__.py       |   0
 .../classifiers/asr_whisper/whisper.py        |  15 +
 nlu/pipe/utils/pipe_utils.py                  |   1 +
 nlu/spellbook.py                              | 190 +++++-
 nlu/universe/annotator_class_universe.py      |   1 +
 nlu/universe/component_universes.py           |  22 +
 nlu/universe/feature_node_ids.py              |   1 +
 nlu/universe/feature_node_universes.py        |   1 +
 .../classifier_tests/asr_tests.py             |  31 +-
 10 files changed, 724 insertions(+), 145 deletions(-)
 create mode 100644 nlu/components/classifiers/asr_whisper/__init__.py
 create mode 100644 nlu/components/classifiers/asr_whisper/whisper.py

diff --git a/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb b/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb
index bfd65402..3899d8a5 100644
--- a/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb
+++ b/examples/colab/component_examples/automatic_speech_recognition/automatic_speech_recognition_overview_ASR.ipynb
@@ -3,8 +3,7 @@
   "nbformat_minor": 0,
   "metadata": {
     "colab": {
-      "provenance": [],
-      "toc_visible": true
+      "provenance": []
     },
     "kernelspec": {
       "name": "python3",
@@ -47,7 +46,7 @@
         "\n",
         "[wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://arxiv.org/pdf/2006.11477.pdf)\n",
         "\n",
-        "you need [librosa](https://librosa.org/doc/latest/index.html) installed to use any audio \n",
+        "you need [librosa](https://librosa.org/doc/latest/index.html) installed to use any audio\n",
         "models with NLU\n",
         "\n",
         "\n",
@@ -67,7 +66,7 @@
       "source": [
         "%%capture\n",
         "! pip install nlu\n",
-        "! pip install pyspark==3.1.1"
+        "! pip install pyspark==3.4.1"
       ]
     },
     {
@@ -82,7 +81,7 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "outputId": "f964c63e-9f2f-41c0-c595-146053858a7b",
+        "outputId": "63660e32-67b5-448f-e043-e64de93f2943",
         "id": "SiJMjhzmhryq"
       },
       "execution_count": 2,
@@ -102,7 +101,7 @@
           "data": {
             "text/plain": [
               "{'wav2vec_for_ctc': Wav2Vec2ForCTC_86f8bcbbea2a,\n",
-              " 'audio_assembler': AudioAssembler_e6070392f6e5}"
+              " 'audio_assembler': AudioAssembler_4df3b8cec472}"
             ]
           },
           "metadata": {},
@@ -113,10 +112,10 @@
     {
       "cell_type": "code",
       "source": [
-        "# Lets download an audio file \n",
+        "# Lets download an audio file\n",
         "!wget https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/audio/samples/wavs/ngm_12484_01067234848.wav\n",
         "\n",
-        "# Lets listen to it \n",
+        "# Lets listen to it\n",
         "from IPython.display import Audio\n",
         "FILE_PATH = \"ngm_12484_01067234848.wav\"\n",
         "Audio(filename=FILE_PATH)"
@@ -125,9 +124,9 @@
         "id": "1WJEzD0ahryq",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 276
+          "height": 266
         },
-        "outputId": "def39094-8fea-4dcf-82c8-f849ad4f9e8f"
+        "outputId": "958a1931-75bc-4328-c863-adc75cce92db"
       },
       "execution_count": 3,
       "outputs": [
@@ -135,16 +134,16 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "--2023-03-20 15:43:41--  https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/audio/samples/wavs/ngm_12484_01067234848.wav\n",
-            "Resolving s3.amazonaws.com (s3.amazonaws.com)... 54.231.160.248, 52.216.147.126, 52.216.112.253, ...\n",
-            "Connecting to s3.amazonaws.com (s3.amazonaws.com)|54.231.160.248|:443... connected.\n",
+            "--2023-11-17 09:19:37--  https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/resources/en/audio/samples/wavs/ngm_12484_01067234848.wav\n",
+            "Resolving s3.amazonaws.com (s3.amazonaws.com)... 54.231.165.48, 16.182.103.136, 52.217.160.96, ...\n",
+            "Connecting to s3.amazonaws.com (s3.amazonaws.com)|54.231.165.48|:443... connected.\n",
             "HTTP request sent, awaiting response... 200 OK\n",
             "Length: 417836 (408K) [audio/wav]\n",
             "Saving to: ‘ngm_12484_01067234848.wav’\n",
             "\n",
-            "ngm_12484_010672348 100%[===================>] 408.04K  --.-KB/s    in 0.08s   \n",
+            "ngm_12484_010672348 100%[===================>] 408.04K  --.-KB/s    in 0.09s   \n",
             "\n",
-            "2023-03-20 15:43:42 (5.03 MB/s) - ‘ngm_12484_01067234848.wav’ saved [417836/417836]\n",
+            "2023-11-17 09:19:37 (4.23 MB/s) - ‘ngm_12484_01067234848.wav’ saved [417836/417836]\n",
             "\n"
           ]
         },
@@ -179,9 +178,9 @@
         "id": "ZpOQwr-6hryq",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 117
+          "height": 115
         },
-        "outputId": "b9f0c6b7-9156-4dbb-f99f-1f67a9b9baec"
+        "outputId": "94d145f7-eae0-4760-e75f-350824bbd83f"
       },
       "execution_count": 4,
       "outputs": [
@@ -205,9 +204,8 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-c783a5ac-7700-4317-a552-87ded080b5a0\">\n",
-              "    <div class=\"colab-df-container\">\n",
-              "      <div>\n",
+              "  <div id=\"df-560bc866-26c4-4f2c-bf53-684edefa7c2d\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -238,21 +236,21 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c783a5ac-7700-4317-a552-87ded080b5a0')\"\n",
-              "              title=\"Convert this dataframe to an interactive table.\"\n",
-              "              style=\"display:none;\">\n",
-              "        \n",
-              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "       width=\"24px\">\n",
-              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
-              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-560bc866-26c4-4f2c-bf53-684edefa7c2d')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
               "  </svg>\n",
-              "      </button>\n",
-              "      \n",
+              "    </button>\n",
+              "\n",
               "  <style>\n",
               "    .colab-df-container {\n",
               "      display:flex;\n",
-              "      flex-wrap:wrap;\n",
               "      gap: 12px;\n",
               "    }\n",
               "\n",
@@ -274,6 +272,10 @@
               "      fill: #174EA6;\n",
               "    }\n",
               "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
               "    [theme=dark] .colab-df-convert {\n",
               "      background-color: #3B4455;\n",
               "      fill: #D2E3FC;\n",
@@ -287,33 +289,34 @@
               "    }\n",
               "  </style>\n",
               "\n",
-              "      <script>\n",
-              "        const buttonEl =\n",
-              "          document.querySelector('#df-c783a5ac-7700-4317-a552-87ded080b5a0 button.colab-df-convert');\n",
-              "        buttonEl.style.display =\n",
-              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-560bc866-26c4-4f2c-bf53-684edefa7c2d button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
-              "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-c783a5ac-7700-4317-a552-87ded080b5a0');\n",
-              "          const dataTable =\n",
-              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                     [key], {});\n",
-              "          if (!dataTable) return;\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-560bc866-26c4-4f2c-bf53-684edefa7c2d');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
               "\n",
-              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "            + ' to learn more about interactive tables.';\n",
-              "          element.innerHTML = '';\n",
-              "          dataTable['output_type'] = 'display_data';\n",
-              "          await google.colab.output.renderOutput(dataTable, element);\n",
-              "          const docLink = document.createElement('div');\n",
-              "          docLink.innerHTML = docLinkHtml;\n",
-              "          element.appendChild(docLink);\n",
-              "        }\n",
-              "      </script>\n",
-              "    </div>\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
               "  </div>\n",
-              "  "
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ]
           },
           "metadata": {},
@@ -330,9 +333,9 @@
         "id": "HNIfZRQMOkle",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 36
+          "height": 35
         },
-        "outputId": "afa48f60-6e34-4599-9f19-27604757df0f"
+        "outputId": "699d0f0c-ecc9-4050-fd02-e6b3572db95c"
       },
       "execution_count": 5,
       "outputs": [
@@ -401,14 +404,14 @@
         "cellView": "form",
         "id": "FeuttsEAaAcY"
       },
-      "execution_count": 6,
+      "execution_count": null,
       "outputs": []
     },
     {
       "cell_type": "code",
       "source": [
         "# We can use this function to record our voice in Google Colab via Mic\n",
-        "# and write it to a wav file for the ASR model \n",
+        "# and write it to a wav file for the ASR model\n",
         "record(10,'my_recording.wav')"
       ],
       "metadata": {
@@ -419,7 +422,7 @@
         },
         "outputId": "66eba143-6761-45da-e456-acdda19198b4"
       },
-      "execution_count": 21,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -484,11 +487,11 @@
         "id": "u43I08KBcpKU",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 54
+          "height": 53
         },
-        "outputId": "0b7faad8-69ce-49ad-c4b6-b5b651c56a57"
+        "outputId": "a0d52374-7974-4a35-b440-bd7e4e895bdf"
       },
-      "execution_count": 22,
+      "execution_count": 6,
       "outputs": [
         {
           "output_type": "stream",
@@ -508,7 +511,7 @@
             }
           },
           "metadata": {},
-          "execution_count": 22
+          "execution_count": 6
         }
       ]
     },
@@ -517,7 +520,7 @@
       "source": [
         "## Hubert\n",
         "HuBERT models  match or surpass the SOTA approaches for speech representation learning for speech recognition, generation, and compression. The Hidden-Unit BERT (HuBERT) approach was proposed for self-supervised speech representation learning, which utilizes an offline clustering step to provide aligned target labels for a BERT-like prediction loss.      \n",
-        "These Models is powered by Spark-NLP's [HubertForCTC Annotator](https://nlp.johnsnowlabs.com/docs/en/transformers#hubertforctc) \n",
+        "These Models is powered by Spark-NLP's [HubertForCTC Annotator](https://nlp.johnsnowlabs.com/docs/en/transformers#hubertforctc)\n",
         "\n",
         "\n",
         "![HUBERT](https://user-images.githubusercontent.com/5762953/217865459-375756c3-a110-4917-8319-1deecb55304d.png)\n",
@@ -540,9 +543,9 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "outputId": "891b11a7-6598-4572-c83b-331eb9603548"
+        "outputId": "4e043691-f455-4b14-f66b-cec3c67279c4"
       },
-      "execution_count": 23,
+      "execution_count": 7,
       "outputs": [
         {
           "output_type": "stream",
@@ -560,18 +563,18 @@
           "data": {
             "text/plain": [
               "{'hubert_for_ctc': HubertForCTC_a3ec8e84d8ed,\n",
-              " 'audio_assembler': AudioAssembler_234f1b9f37fa}"
+              " 'audio_assembler': AudioAssembler_1f178382078f}"
             ]
           },
           "metadata": {},
-          "execution_count": 23
+          "execution_count": 7
         }
       ]
     },
     {
       "cell_type": "code",
       "source": [
-        "# Lets test on the recording we just used \n",
+        "# Lets test on the recording we just used\n",
         "asr_df = hubert.predict('my_recording.wav')\n",
         "asr_df"
       ],
@@ -579,11 +582,11 @@
         "id": "ogZqAVPeo8H8",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 117
+          "height": 115
         },
-        "outputId": "6cc20a8a-2f2a-4b41-9b49-b5171d4e063e"
+        "outputId": "fe650639-4d83-4fed-96f6-a597e12ce34a"
       },
-      "execution_count": 24,
+      "execution_count": 8,
       "outputs": [
         {
           "output_type": "stream",
@@ -598,16 +601,15 @@
           "data": {
             "text/plain": [
               "                                        audio_series  \\\n",
-              "0  [-7.275957614183426e-12, -3.2741809263825417e-...   \n",
+              "0  [-3.67435859516263e-10, -3.0377123039215803e-1...   \n",
               "\n",
               "                                                text  \n",
               "0  RUN THIS CEL TO RECORD YOUR VOICE IT WIL BE WR...  "
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-2fb89a4b-2629-40d8-8271-24b0ed6d30d4\">\n",
-              "    <div class=\"colab-df-container\">\n",
-              "      <div>\n",
+              "  <div id=\"df-fcd85c8e-d1ed-41f8-a68a-4a9f94e0a315\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -632,27 +634,27 @@
               "  <tbody>\n",
               "    <tr>\n",
               "      <th>0</th>\n",
-              "      <td>[-7.275957614183426e-12, -3.2741809263825417e-...</td>\n",
+              "      <td>[-3.67435859516263e-10, -3.0377123039215803e-1...</td>\n",
               "      <td>RUN THIS CEL TO RECORD YOUR VOICE IT WIL BE WR...</td>\n",
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2fb89a4b-2629-40d8-8271-24b0ed6d30d4')\"\n",
-              "              title=\"Convert this dataframe to an interactive table.\"\n",
-              "              style=\"display:none;\">\n",
-              "        \n",
-              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "       width=\"24px\">\n",
-              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
-              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fcd85c8e-d1ed-41f8-a68a-4a9f94e0a315')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
               "  </svg>\n",
-              "      </button>\n",
-              "      \n",
+              "    </button>\n",
+              "\n",
               "  <style>\n",
               "    .colab-df-container {\n",
               "      display:flex;\n",
-              "      flex-wrap:wrap;\n",
               "      gap: 12px;\n",
               "    }\n",
               "\n",
@@ -674,6 +676,10 @@
               "      fill: #174EA6;\n",
               "    }\n",
               "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
               "    [theme=dark] .colab-df-convert {\n",
               "      background-color: #3B4455;\n",
               "      fill: #D2E3FC;\n",
@@ -687,37 +693,38 @@
               "    }\n",
               "  </style>\n",
               "\n",
-              "      <script>\n",
-              "        const buttonEl =\n",
-              "          document.querySelector('#df-2fb89a4b-2629-40d8-8271-24b0ed6d30d4 button.colab-df-convert');\n",
-              "        buttonEl.style.display =\n",
-              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-fcd85c8e-d1ed-41f8-a68a-4a9f94e0a315 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
-              "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-2fb89a4b-2629-40d8-8271-24b0ed6d30d4');\n",
-              "          const dataTable =\n",
-              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                     [key], {});\n",
-              "          if (!dataTable) return;\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-fcd85c8e-d1ed-41f8-a68a-4a9f94e0a315');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
               "\n",
-              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "            + ' to learn more about interactive tables.';\n",
-              "          element.innerHTML = '';\n",
-              "          dataTable['output_type'] = 'display_data';\n",
-              "          await google.colab.output.renderOutput(dataTable, element);\n",
-              "          const docLink = document.createElement('div');\n",
-              "          docLink.innerHTML = docLinkHtml;\n",
-              "          element.appendChild(docLink);\n",
-              "        }\n",
-              "      </script>\n",
-              "    </div>\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
               "  </div>\n",
-              "  "
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ]
           },
           "metadata": {},
-          "execution_count": 24
+          "execution_count": 8
         }
       ]
     },
@@ -725,7 +732,7 @@
       "cell_type": "code",
       "source": [
         "# Lets record something new and ASR it\n",
-        "record(10,'my_recording.wav')\n"
+        "record(10,'my_recording2.wav')\n"
       ],
       "metadata": {
         "id": "KCVK0mc7d0z4",
@@ -735,7 +742,7 @@
         },
         "outputId": "01c0bff2-5777-4790-b1c5-a3ede94a5af5"
       },
-      "execution_count": 25,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -793,19 +800,26 @@
     {
       "cell_type": "code",
       "source": [
-        "asr_df = hubert.predict('my_recording.wav')\n",
+        "asr_df = hubert.predict('my_recording2.wav')\n",
         "asr_df.text.values[0]"
       ],
       "metadata": {
         "id": "EVX9bQ4yd9SW",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 36
+          "height": 53
         },
-        "outputId": "64f29149-1638-4892-998b-97db967eb5c9"
+        "outputId": "3e2bed0f-1bda-4107-ce3d-2deaeb9c9823"
       },
-      "execution_count": 28,
+      "execution_count": 9,
       "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Warning::Spark Session already created, some configs may not take.\n"
+          ]
+        },
         {
           "output_type": "execute_result",
           "data": {
@@ -817,7 +831,257 @@
             }
           },
           "metadata": {},
-          "execution_count": 28
+          "execution_count": 9
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Whisper\n",
+        "Whisper Model with a language modeling head on top for Connectionist Temporal Classification (CTC). Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. It transcribe in multiple languages, as well as translate from those languages into English.    \n",
+        "These Models is powered by Spark-NLP's [WhisperForCTC Annotator](https://sparknlp.org/docs/en/transformers#whisperforctc)\n",
+        "\n",
+        "[Robust Speech Recognition via Large-Scale Weak Supervision](https://arxiv.org/abs/2212.04356)\n",
+        "\n",
+        "Note that at the moment, this annotator only supports greedy search and only Spark Versions 3.4 and up are supported.\n",
+        "\n",
+        "![WhisperForCTC.png](data:image/png;base64,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)"
+      ],
+      "metadata": {
+        "id": "C0Qf_bItgk4b"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import nlu\n",
+        "whisper = nlu.load('xx.speech2text.whisper.tiny')\n",
+        "whisper"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yn5ZBXDQmi6z",
+        "outputId": "274ae9f3-61b6-40cb-ff18-33ebc659a0e2"
+      },
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Warning::Spark Session already created, some configs may not take.\n",
+            "asr_whisper_tiny download started this may take some time.\n",
+            "Approximate size to download 149.4 MB\n",
+            "[OK!]\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{'whisper_for_ctc': WhisperForCTC_b48195b5aa99,\n",
+              " 'audio_assembler': AudioAssembler_fd42e8825a2b}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 1
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "asr_df = whisper.predict('my_recording.wav')\n",
+        "asr_df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 115
+        },
+        "id": "2tfNqgv-mjED",
+        "outputId": "df70d4f1-3f3c-472d-a39d-540cf41642f2"
+      },
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Warning::Spark Session already created, some configs may not take.\n",
+            "Warning::Spark Session already created, some configs may not take.\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                        audio_series  \\\n",
+              "0  [-3.67435859516263e-10, -3.0377123039215803e-1...   \n",
+              "\n",
+              "                                                text  \n",
+              "0   Run the cell to record your voice. It will be...  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-2b1a6b98-7c45-44d8-bef3-9b2ffee21067\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>audio_series</th>\n",
+              "      <th>text</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>[-3.67435859516263e-10, -3.0377123039215803e-1...</td>\n",
+              "      <td>Run the cell to record your voice. It will be...</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2b1a6b98-7c45-44d8-bef3-9b2ffee21067')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-2b1a6b98-7c45-44d8-bef3-9b2ffee21067 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-2b1a6b98-7c45-44d8-bef3-9b2ffee21067');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 2
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "asr_df = whisper.predict('my_recording2.wav')\n",
+        "asr_df.text.values[0]"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 53
+        },
+        "id": "z7Pg8GComjHa",
+        "outputId": "1e16538a-b5ec-47b4-a1d0-9b78fd712c5d"
+      },
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Warning::Spark Session already created, some configs may not take.\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "' There are hundreds of models for dozens of languages. You can play around with. Check them out.'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 3
         }
       ]
     },
@@ -826,7 +1090,7 @@
       "source": [
         "## Try out other models\n",
         "\n",
-        " There are many more wav2vec, wav2vec2, hubert and other models for ASR \n",
+        " There are many more wav2vec, wav2vec2, hubert, whisper and other models for ASR\n",
         "\n",
         " You can try any of them out by simply chaning the parameter of `nlu.load('my_model')` to the one you want to test.\n",
         "\n",
@@ -1876,11 +2140,110 @@
         "| wo         | [wo.speech2text.wav2vec_xlsr.v2_300m_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_av2vec2_xls_r_300m_wolof_lm_gpu_wo.html)                                                                 | [asr_av2vec2_xls_r_300m_wolof_lm_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_av2vec2_xls_r_300m_wolof_lm_gpu_wo.html)                                                                 | Wav2Vec2ForCTC    |\n",
         "| yue        | [yue.speech2text.wav2vec_xlsr.v2_large](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_cantonese_by_ctl_yue.html)                                                             | [asr_wav2vec2_large_xlsr_cantonese_by_ctl](https://nlp.johnsnowlabs.com/2022/09/24/asr_wav2vec2_large_xlsr_cantonese_by_ctl_yue.html)                                                      | Wav2Vec2ForCTC    |\n",
         "| yue        | [yue.speech2text.wav2vec_xlsr.v2_large_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu_yue.html)                                                     | [asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu](https://nlp.johnsnowlabs.com/2022/09/26/asr_wav2vec2_large_xlsr_cantonese_by_ctl_gpu_yue.html)                                              | Wav2Vec2ForCTC    |\n",
+        "|bg      |bg.speech2text.whisper.tiny_bulgarian_l                                          |[asr_whisper_tiny_bulgarian_l](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_tiny_bulgarian_l_bg.html)                                                                                    |WhisperForCTC  |\n",
+        "|cs      |cs.speech2text.whisper.small_czech_cv11                                          |[asr_whisper_small_czech_cv11](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_czech_cv11_cs.html)                                                                                    |WhisperForCTC  |\n",
+        "|da      |da.speech2text.whisper.danish_small_augmented                                    |[asr_whisper_danish_small_augmented](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_danish_small_augmented_da.html)                                                                        |WhisperForCTC  |\n",
+        "|de      |de.speech2text.whisper.small_allsnr                                              |[asr_whisper_small_allsnr](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_allsnr_de.html)                                                                                            |WhisperForCTC  |\n",
+        "|el      |el.speech2text.whisper.samoan_farsipal_e5                                        |[asr_whisper_samoan_farsipal_e5](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_samoan_farsipal_e5_el.html)                                                                                |WhisperForCTC  |\n",
+        "|el      |el.speech2text.whisper.small_greek                                               |[asr_whisper_small_greek](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_greek_el.html)                                                                                              |WhisperForCTC  |\n",
+        "|el      |el.speech2text.whisper.tswana_greek_modern_e1                                    |[asr_whisper_tswana_greek_modern_e1](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_tswana_greek_modern_e1_el.html)                                                                        |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_english_model                                       |[asr_personal_whisper_small_english_model](https://nlp.johnsnowlabs.com/2023/10/19/asr_personal_whisper_small_english_model_en.html)                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.base_bulgarian_l                                          |[asr_whisper_base_bulgarian_l](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_base_bulgarian_l_en.html)                                                                                    |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.base_english                                              |[asr_whisper_base_english](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_base_english_en.html)                                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.base_european                                             |[asr_whisper_base_european](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_base_european_en.html)                                                                                          |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.base_swedish                                              |[asr_whisper_base_swedish](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_base_swedish_en.html)                                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.persian_farsi                                             |[asr_whisper_persian_farsi](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_persian_farsi_en.html)                                                                                          |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_arabic_cv11                                         |[asr_whisper_small_arabic_cv11](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_arabic_cv11_en.html)                                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_bak                                                 |[asr_whisper_small_bak](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_bak_en.html)                                                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_bengali_subhadeep                                   |[asr_whisper_small_bengali_subhadeep](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_bengali_subhadeep_en.html)                                                                      |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_chinese_hk                                          |[asr_whisper_small_chinese_hk](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_chinese_hk_en.html)                                                                                    |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_chinese_tw_voidful                                  |[asr_whisper_small_chinese_tw_voidful](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_chinese_tw_voidful_en.html)                                                                    |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_english                                             |[asr_whisper_small_english](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_english_en.html)                                                                                          |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_english_blueraccoon                                 |[asr_whisper_small_english_blueraccoon](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_english_blueraccoon_en.html)                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_german                                              |[asr_whisper_small_german](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_german_en.html)                                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_hungarian_cv11                                      |[asr_whisper_small_hungarian_cv11](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_hungarian_cv11_en.html)                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_lithuanian_serbian_v2                               |[asr_whisper_small_lithuanian_serbian_v2](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_lithuanian_serbian_v2_en.html)                                                              |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_mongolian_2                                         |[asr_whisper_small_mongolian_2](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_mongolian_2_en.html)                                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_mongolian_3                                         |[asr_whisper_small_mongolian_3](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_mongolian_3_en.html)                                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_portuguese_yapeng                                   |[asr_whisper_small_portuguese_yapeng](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_portuguese_yapeng_en.html)                                                                      |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_se2                                                 |[asr_whisper_small_se2](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_se2_en.html)                                                                                                  |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_spanish_1e_6                                        |[asr_whisper_small_spanish_1e_6](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_spanish_1e_6_en.html)                                                                                |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_swe2                                                |[asr_whisper_small_swe2](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_swe2_en.html)                                                                                                |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_swe_davidt123                                       |[asr_whisper_small_swe_davidt123](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_swe_davidt123_en.html)                                                                              |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_swedish_se_afroanton                                |[asr_whisper_small_swedish_se_afroanton](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_swedish_se_afroanton_en.html)                                                                |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_telugu_openslr                                      |[asr_whisper_small_telugu_openslr](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_telugu_openslr_en.html)                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_tonga_zambia                                        |[asr_whisper_small_tonga_zambia](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_tonga_zambia_en.html)                                                                                |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.small_urdu_1000_64_1e_05_pretrain_arabic                  |[asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en.html)                                    |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.testrun1                                                  |[asr_whisper_testrun1](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_testrun1_en.html)                                                                                                    |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_english                                              |[asr_whisper_tiny_english](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_tiny_english_en.html)                                                                                            |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_european                                             |[asr_whisper_tiny_european](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_tiny_european_en.html)                                                                                          |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_german                                               |[asr_whisper_tiny_german](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_tiny_german_en.html)                                                                                              |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_italian_local                                        |[asr_whisper_tiny_italian_local](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_tiny_italian_local_en.html)                                                                                |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_pashto                                               |[asr_whisper_tiny_pashto](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_tiny_pashto_en.html)                                                                                              |WhisperForCTC  |\n",
+        "|en      |en.speech2text.whisper.tiny_tgl                                                  |[asr_whisper_tiny_tgl](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_tiny_tgl_en.html)                                                                                                    |WhisperForCTC  |\n",
+        "|es      |es.speech2text.whisper.small_spanish_ari                                         |[asr_whisper_small_spanish_ari](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_spanish_ari_es.html)                                                                                  |WhisperForCTC  |\n",
+        "|es      |es.speech2text.whisper.tiny_spanish_arpagon                                      |[asr_whisper_tiny_spanish_arpagon](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_tiny_spanish_arpagon_es.html)                                                                            |WhisperForCTC  |\n",
+        "|fi      |fi.speech2text.whisper.small_finnish_15k_samples                                 |[asr_whisper_small_finnish_15k_samples](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_finnish_15k_samples_fi.html)                                                                  |WhisperForCTC  |\n",
+        "|fi      |fi.speech2text.whisper.small_finnish_sgangireddy                                 |[asr_whisper_small_finnish_sgangireddy](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_finnish_sgangireddy_fi.html)                                                                  |WhisperForCTC  |\n",
+        "|fr      |fr.speech2text.whisper.small_defined_dot_ai_qc_french_combined_dataset_normalized|[asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr.html)|WhisperForCTC  |\n",
+        "|hi      |hi.speech2text.whisper.small_french_yocel1                                       |[asr_whisper_small_french_yocel1](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_french_yocel1_hi.html)                                                                              |WhisperForCTC  |\n",
+        "|hi      |hi.speech2text.whisper.small_hindi_norwegian_tensorboard                         |[asr_whisper_small_hindi_norwegian_tensorboard](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_hindi_norwegian_tensorboard_hi.html)                                                  |WhisperForCTC  |\n",
+        "|hi      |hi.speech2text.whisper.small_hindi_shripadbhat                                   |[asr_whisper_small_hindi_shripadbhat](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_hindi_shripadbhat_hi.html)                                                                      |WhisperForCTC  |\n",
+        "|hi      |hi.speech2text.whisper.small_hindi_xinhuang                                      |[asr_whisper_small_hindi_xinhuang](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_hindi_xinhuang_hi.html)                                                                            |WhisperForCTC  |\n",
+        "|hy      |hy.speech2text.whisper.small_armenian                                            |[asr_whisper_small_armenian](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_armenian_hy.html)                                                                                        |WhisperForCTC  |\n",
+        "|it      |it.speech2text.whisper.small_italian_3                                           |[asr_whisper_small_italian_3](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_italian_3_it.html)                                                                                      |WhisperForCTC  |\n",
+        "|it      |it.speech2text.whisper.tiny_italian_1                                            |[asr_whisper_tiny_italian_1](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_tiny_italian_1_it.html)                                                                                        |WhisperForCTC  |\n",
+        "|it      |it.speech2text.whisper.tiny_italian_2                                            |[asr_whisper_tiny_italian_2](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_tiny_italian_2_it.html)                                                                                        |WhisperForCTC  |\n",
+        "|ja      |ja.speech2text.whisper.small_japanese_jakeyoo                                    |[asr_whisper_small_japanese_jakeyoo](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_japanese_jakeyoo_ja.html)                                                                        |WhisperForCTC  |\n",
+        "|ja      |ja.speech2text.whisper.small_japanese_vumichien                                  |[asr_whisper_small_japanese_vumichien](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_japanese_vumichien_ja.html)                                                                    |WhisperForCTC  |\n",
+        "|kn      |kn.speech2text.whisper.kannada_base                                              |[asr_whisper_kannada_base](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_kannada_base_kn.html)                                                                                            |WhisperForCTC  |\n",
+        "|kn      |kn.speech2text.whisper.kannada_small                                             |[asr_whisper_kannada_small](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_kannada_small_kn.html)                                                                                          |WhisperForCTC  |\n",
+        "|ko      |ko.speech2text.whisper.small_korean_fl                                           |[asr_whisper_small_korean_fl](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_korean_fl_ko.html)                                                                                      |WhisperForCTC  |\n",
+        "|lt      |lt.speech2text.whisper.lithuanian_finetune                                       |[asr_whisper_lithuanian_finetune](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_lithuanian_finetune_lt.html)                                                                              |WhisperForCTC  |\n",
+        "|lt      |lt.speech2text.whisper.small_lithuanian_deividasm                                |[asr_whisper_small_lithuanian_deividasm](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_lithuanian_deividasm_lt.html)                                                                |WhisperForCTC  |\n",
+        "|ml      |ml.speech2text.whisper.malayalam_first_model                                     |[asr_whisper_malayalam_first_model](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_malayalam_first_model_ml.html)                                                                          |WhisperForCTC  |\n",
+        "|mn      |mn.speech2text.whisper.small_mongolian_1                                         |[asr_whisper_small_mongolian_1](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_mongolian_1_mn.html)                                                                                  |WhisperForCTC  |\n",
+        "|ne      |ne.speech2text.whisper.small_nepali_np                                           |[asr_whisper_small_nepali_np](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_nepali_np_ne.html)                                                                                      |WhisperForCTC  |\n",
+        "|nl      |nl.speech2text.whisper.small_dutch                                               |[asr_whisper_small_dutch](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_dutch_nl.html)                                                                                              |WhisperForCTC  |\n",
+        "|no      |no.speech2text.whisper.small_nob                                                 |[asr_whisper_small_nob](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_nob_no.html)                                                                                                  |WhisperForCTC  |\n",
+        "|pa      |pa.speech2text.whisper.small_punjabi_eastern                                     |[asr_whisper_small_punjabi_eastern](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_punjabi_eastern_pa.html)                                                                          |WhisperForCTC  |\n",
+        "|pl      |pl.speech2text.whisper.small_polish_aspik101                                     |[asr_whisper_small_polish_aspik101](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_polish_aspik101_pl.html)                                                                          |WhisperForCTC  |\n",
+        "|pl      |pl.speech2text.whisper.tiny_polish                                               |[asr_whisper_tiny_polish](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_tiny_polish_pl.html)                                                                                              |WhisperForCTC  |\n",
+        "|ps      |ps.speech2text.whisper.small_pashto_ihanif                                       |[asr_whisper_small_pashto_ihanif](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_pashto_ihanif_ps.html)                                                                              |WhisperForCTC  |\n",
+        "|sv      |sv.speech2text.whisper.small_swedish_english                                     |[asr_whisper_small_swedish_english](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_swedish_english_se.html)                                                                          |WhisperForCTC  |\n",
+        "|sv      |sv.speech2text.whisper.small_swedish_test_3000                                   |[asr_whisper_small_swedish_test_3000](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_swedish_test_3000_sv.html)                                                                      |WhisperForCTC  |\n",
+        "|sv      |sv.speech2text.whisper.small_swedish_torileatherman                              |[asr_whisper_small_swedish_torileatherman](https://nlp.johnsnowlabs.com/2023/10/20/asr_whisper_small_swedish_torileatherman_sv.html)                                                            |WhisperForCTC  |\n",
+        "|sw      |sw.speech2text.whisper.small_swahili_pplantinga                                  |[asr_whisper_small_swahili_pplantinga](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_swahili_pplantinga_sw.html)                                                                    |WhisperForCTC  |\n",
+        "|ta      |ta.speech2text.whisper.tiny_tamil_example                                        |[asr_whisper_tiny_tamil_example](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_tiny_tamil_example_ta.html)                                                                                |WhisperForCTC  |\n",
+        "|te      |te.speech2text.whisper.small_telugu_146h                                         |[asr_whisper_small_telugu_146h](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_telugu_146h_te.html)                                                                                  |WhisperForCTC  |\n",
+        "|te      |te.speech2text.whisper.telugu_tiny                                               |[asr_whisper_telugu_tiny](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_telugu_tiny_te.html)                                                                                              |WhisperForCTC  |\n",
+        "|th      |th.speech2text.whisper.small_thai_napatswift                                     |[asr_whisper_small_thai_napatswift](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_thai_napatswift_th.html)                                                                          |WhisperForCTC  |\n",
+        "|tt      |tt.speech2text.whisper.small_tatar                                               |[asr_whisper_small_tatar](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_tatar_tt.html)                                                                                              |WhisperForCTC  |\n",
+        "|uk      |uk.speech2text.whisper.small_ukrainian                                           |[asr_whisper_small_ukrainian](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_ukrainian_uk.html)                                                                                      |WhisperForCTC  |\n",
+        "|uz      |uz.speech2text.whisper.small_uzbek                                               |[asr_whisper_small_uzbek](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_uzbek_uz.html)                                                                                              |WhisperForCTC  |\n",
+        "|vi      |vi.speech2text.whisper.small_vietnamese_tuananh7198                              |[asr_whisper_small_vietnamese_tuananh7198](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_vietnamese_tuananh7198_vi.html)                                                            |WhisperForCTC  |\n",
+        "|xx      |xx.speech2text.whisper.base                                                      |[asr_whisper_base](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_base_xx.html)                                                                                                            |WhisperForCTC  |\n",
+        "|xx      |xx.speech2text.whisper.base_bengali_trans                                        |[asr_whisper_base_bengali_trans](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_base_bengali_trans_xx.html)                                                                                |WhisperForCTC  |\n",
+        "|xx      |xx.speech2text.whisper.small                                                     |[asr_whisper_small](https://nlp.johnsnowlabs.com/2023/10/17/asr_whisper_small_xx.html)                                                                                                          |WhisperForCTC  |\n",
+        "|xx      |xx.speech2text.whisper.tiny                                                      |[asr_whisper_tiny](https://nlp.johnsnowlabs.com/2023/08/22/asr_whisper_tiny_xx.html)                                                                                                            |WhisperForCTC  |\n",
+        "|xx      |xx.speech2text.whisper.tiny_opt                                                  |[asr_whisper_tiny_opt](https://nlp.johnsnowlabs.com/2023/08/22/asr_whisper_tiny_opt_xx.html)                                                                                                    |WhisperForCTC  |\n",
+        "|zh      |zh.speech2text.whisper.small_chinese                                             |[asr_whisper_small_chinese](https://nlp.johnsnowlabs.com/2023/10/18/asr_whisper_small_chinese_zh.html)                                                                                          |WhisperForCTC  |\n",
+        "|zh      |zh.speech2text.whisper.small_chinesebasetw                                       |[asr_whisper_small_chinesebasetw](https://nlp.johnsnowlabs.com/2023/10/19/asr_whisper_small_chinesebasetw_zh.html)                                                                              |WhisperForCTC  |\n",
+        "\n",
         "\n"
       ],
       "metadata": {
         "id": "67j5H7wkhfGe"
       }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "VrRvcjpIoRyl"
+      },
+      "execution_count": null,
+      "outputs": []
     }
   ]
 }
\ No newline at end of file
diff --git a/nlu/components/classifiers/asr_whisper/__init__.py b/nlu/components/classifiers/asr_whisper/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/nlu/components/classifiers/asr_whisper/whisper.py b/nlu/components/classifiers/asr_whisper/whisper.py
new file mode 100644
index 00000000..65d30367
--- /dev/null
+++ b/nlu/components/classifiers/asr_whisper/whisper.py
@@ -0,0 +1,15 @@
+from sparknlp.annotator import *
+
+
+class Whisper:
+    @staticmethod
+    def get_default_model():
+        return WhisperForCTC.pretrained() \
+            .setInputCols("audio_assembler") \
+            .setOutputCol("text")
+
+    @staticmethod
+    def get_pretrained_model(name, language, bucket=None):
+        return WhisperForCTC.pretrained(name, language, bucket) \
+            .setInputCols("audio_assembler") \
+            .setOutputCol("text")
\ No newline at end of file
diff --git a/nlu/pipe/utils/pipe_utils.py b/nlu/pipe/utils/pipe_utils.py
index 505d7381..80648d3b 100644
--- a/nlu/pipe/utils/pipe_utils.py
+++ b/nlu/pipe/utils/pipe_utils.py
@@ -681,6 +681,7 @@ def add_metadata_to_pipe(pipe: NLUPipeline):
             if c.license == Licenses.open_source \
                     and c.name != NLP_NODE_IDS.WAV2VEC_FOR_CTC \
                     and c.name != NLP_NODE_IDS.HUBERT_FOR_CTC \
+                    and c.name != NLP_NODE_IDS.WHISPER_FOR_CTC \
                     and c.name != NLP_NODE_IDS.AUDIO_ASSEMBLER:
                 # TODO Table Assembler/VIT/ Other non txt open source
                 pipe.has_nlp_components = True
diff --git a/nlu/spellbook.py b/nlu/spellbook.py
index d58b9796..2ff30a23 100644
--- a/nlu/spellbook.py
+++ b/nlu/spellbook.py
@@ -1943,6 +1943,7 @@ class Spellbook:
                'bg.pos.ud_btb': 'pos_ud_btb',
                'bg.speech2text.wav2vec_xlsr.v2_large_300m': 'asr_wav2vec2_large_xls_r_300m_d2',
                'bg.speech2text.wav2vec_xlsr.v2_large_300m_d2_gpu': 'asr_wav2vec2_large_xls_r_300m_d2_gpu',
+               'bg.speech2text.whisper.tiny_bulgarian_l': 'asr_whisper_tiny_bulgarian_l',
                'bg.stopwords': 'stopwords_iso',
                'bg.stopwords.iso': 'stopwords_iso'},
         'bh': {'bh.embed.w2v_cc_300d': 'w2v_cc_300d',
@@ -2039,6 +2040,7 @@ class Spellbook:
                'cs.speech2text.wav2vec_xlsr.v2_large': 'asr_wav2vec2_large_xlsr_53_czech',
                'cs.speech2text.wav2vec_xlsr.v2_large.by_arampacha': 'asr_wav2vec2_large_xlsr_czech',
                'cs.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_53_czech_gpu',
+               'cs.speech2text.whisper.small_czech_cv11': 'asr_whisper_small_czech_cv11',
                'cs.stopwords': 'stopwords_iso',
                'cs.stopwords.iso': 'stopwords_iso'},
         'cu': {'cu.lemma': 'lemma_proiel',
@@ -2088,6 +2090,7 @@ class Spellbook:
                'da.speech2text.wav2vec_xlsr.300m.by_chcaa': 'asr_xls_r_300m_nst_cv9',
                'da.speech2text.wav2vec_xlsr.300m_gpu': 'asr_xls_r_300m_nst_cv9_gpu',
                'da.speech2text.wav2vec_xlsr.v2_300m': 'asr_wav2vec2_xls_r_300m_ftspeech',
+               'da.speech2text.whisper.danish_small_augmented': 'asr_whisper_danish_small_augmented',
                'da.stopwords': 'stopwords_iso'},
         'de': {'de.answer_question.bert': 'bert_qa_GBERTQnA',
                'de.answer_question.bert.cased_multilingual_base': 'bert_qa_multilingual_bert_base_cased_german',
@@ -2377,6 +2380,7 @@ class Spellbook:
                'de.speech2text.wav2vec_xlsr.v2_s728_exp': 'asr_exp_w2v2r_xls_r_accent_germany_10_austria_0_s728',
                'de.speech2text.wav2vec_xlsr.v2_s886_exp': 'asr_exp_w2v2r_xls_r_accent_germany_10_austria_0_s886',
                'de.speech2text.wav2vec_xlsr.v3_large.by_marcel': 'asr_wav2vec2_large_xlsr_german_demo',
+               'de.speech2text.whisper.small_allsnr': 'asr_whisper_small_allsnr',
                'de.stopwords': 'stopwords_iso',
                'de.stopwords.iso': 'stopwords_iso'},
         'diq': {'diq.embed.w2v_cc_300d': 'w2v_cc_300d'},
@@ -2423,6 +2427,9 @@ class Spellbook:
                'el.speech2text.wav2vec_xlsr.v2_large_gpu.by_skylord': 'asr_wav2vec2_large_xlsr_greek_1_gpu',
                'el.speech2text.wav2vec_xlsr.v3_large.by_skylord': 'asr_wav2vec2_large_xlsr_greek_2',
                'el.speech2text.wav2vec_xlsr.v3_large_gpu.by_skylord': 'asr_wav2vec2_large_xlsr_greek_2_gpu',
+               'el.speech2text.whisper.samoan_farsipal_e5': 'asr_whisper_samoan_farsipal_e5',
+               'el.speech2text.whisper.small_greek': 'asr_whisper_small_greek',
+               'el.speech2text.whisper.tswana_greek_modern_e1': 'asr_whisper_tswana_greek_modern_e1',
                'el.stopwords': 'stopwords_iso',
                'el.stopwords.iso': 'stopwords_iso'},
         'eml': {'eml.embed.w2v_cc_300d': 'w2v_cc_300d'},
@@ -6576,6 +6583,40 @@ class Spellbook:
             'en.speech2text.wav2vec_xlsr.v2_multilingual': 'asr_wav2vec2_xlsr_multilingual_53',
             'en.speech2text.wav2vec_xlsr.v2_multilingual_gpu': 'asr_wav2vec2_xlsr_multilingual_53_gpu',
             'en.speech2text.wav2vec_xlsr.v2gpu.by_bakhtullah123': 'asr_xlsr_training_gpu',
+            'en.speech2text.whisper.small_english_model': 'asr_personal_whisper_small_english_model',
+            'en.speech2text.whisper.base_bulgarian_l': 'asr_whisper_base_bulgarian_l',
+            'en.speech2text.whisper.base_english': 'asr_whisper_base_english',
+            'en.speech2text.whisper.base_european': 'asr_whisper_base_european',
+            'en.speech2text.whisper.base_swedish': 'asr_whisper_base_swedish',
+            'en.speech2text.whisper.persian_farsi': 'asr_whisper_persian_farsi',
+            'en.speech2text.whisper.small_arabic_cv11': 'asr_whisper_small_arabic_cv11',
+            'en.speech2text.whisper.small_bak': 'asr_whisper_small_bak',
+            'en.speech2text.whisper.small_bengali_subhadeep': 'asr_whisper_small_bengali_subhadeep',
+            'en.speech2text.whisper.small_chinese_hk': 'asr_whisper_small_chinese_hk',
+            'en.speech2text.whisper.small_chinese_tw_voidful': 'asr_whisper_small_chinese_tw_voidful',
+            'en.speech2text.whisper.small_english': 'asr_whisper_small_english',
+            'en.speech2text.whisper.small_english_blueraccoon': 'asr_whisper_small_english_blueraccoon',
+            'en.speech2text.whisper.small_german': 'asr_whisper_small_german',
+            'en.speech2text.whisper.small_hungarian_cv11': 'asr_whisper_small_hungarian_cv11',
+            'en.speech2text.whisper.small_lithuanian_serbian_v2': 'asr_whisper_small_lithuanian_serbian_v2',
+            'en.speech2text.whisper.small_mongolian_2': 'asr_whisper_small_mongolian_2',
+            'en.speech2text.whisper.small_mongolian_3': 'asr_whisper_small_mongolian_3',
+            'en.speech2text.whisper.small_portuguese_yapeng': 'asr_whisper_small_portuguese_yapeng',
+            'en.speech2text.whisper.small_se2': 'asr_whisper_small_se2',
+            'en.speech2text.whisper.small_spanish_1e_6': 'asr_whisper_small_spanish_1e_6',
+            'en.speech2text.whisper.small_swe2': 'asr_whisper_small_swe2',
+            'en.speech2text.whisper.small_swe_davidt123': 'asr_whisper_small_swe_davidt123',
+            'en.speech2text.whisper.small_swedish_se_afroanton': 'asr_whisper_small_swedish_se_afroanton',
+            'en.speech2text.whisper.small_telugu_openslr': 'asr_whisper_small_telugu_openslr',
+            'en.speech2text.whisper.small_tonga_zambia': 'asr_whisper_small_tonga_zambia',
+            'en.speech2text.whisper.small_urdu_1000_64_1e_05_pretrain_arabic': 'asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic',
+            'en.speech2text.whisper.testrun1': 'asr_whisper_testrun1',
+            'en.speech2text.whisper.tiny_english': 'asr_whisper_tiny_english',
+            'en.speech2text.whisper.tiny_european': 'asr_whisper_tiny_european',
+            'en.speech2text.whisper.tiny_german': 'asr_whisper_tiny_german',
+            'en.speech2text.whisper.tiny_italian_local': 'asr_whisper_tiny_italian_local',
+            'en.speech2text.whisper.tiny_pashto': 'asr_whisper_tiny_pashto',
+            'en.speech2text.whisper.tiny_tgl': 'asr_whisper_tiny_tgl',
             'en.spell.norvig': 'spellcheck_norvig',
             'en.stem': 'stemmer',
             'en.stopwords': 'stopwords_iso',
@@ -6807,6 +6848,8 @@ class Spellbook:
             'es.pos.roberta_base_bne_capitel_pos': 'roberta_pos_roberta_base_bne_capitel_pos',
             'es.pos.roberta_large_bne_capitel_pos': 'roberta_pos_roberta_large_bne_capitel_pos',
             'es.pos.ud_gsd': 'pos_ud_gsd',
+            'es.speech2text.whisper.small_spanish_ari': 'asr_whisper_small_spanish_ari',
+            'es.speech2text.whisper.tiny_spanish_arpagon': 'asr_whisper_tiny_spanish_arpagon',
             'es.stopwords': 'stopwords_iso',
             'es.stopwords_es': 'stopwords_es'},
         'et': {'et.answer_question.xlm_roberta': 'xlm_roberta_qa_xlm_roberta_est_qa',
@@ -6988,6 +7031,8 @@ class Spellbook:
                'fi.speech2text.wav2vec_xlsr.v2_large_gpu.by_jonatasgrosman': 'asr_wav2vec2_large_xlsr_53_finnish_by_jonatasgrosman_gpu',
                'fi.speech2text.wav2vec_xlsr.v2_large_gpu.by_vasilis': 'asr_wav2vec2_large_xlsr_53_finnish_by_vasilis_gpu',
                'fi.speech2text.wav2vec_xlsrby_aapot': 'asr_wav2vec2_xlsr_1b_finnish_lm_by_aapot',
+               'fi.speech2text.whisper.small_finnish_15k_samples': 'asr_whisper_small_finnish_15k_samples',
+               'fi.speech2text.whisper.small_finnish_sgangireddy': 'asr_whisper_small_finnish_sgangireddy',
                'fi.stopwords': 'stopwords_iso',
                'fi.stopwords.iso': 'stopwords_iso'},
         'fo': {'fo.lemma': 'lemma_farpahc',
@@ -7242,6 +7287,7 @@ class Spellbook:
             'fr.speech2text.wav2vec_xlsr.v2_s286_exp': 'asr_exp_w2v2t_xlsr_53_s286',
             'fr.speech2text.wav2vec_xlsr.v2_s539_exp': 'asr_exp_w2v2t_xlsr_53_s539',
             'fr.speech2text.wav2vec_xlsr.v2_s800_exp': 'asr_exp_w2v2t_xlsr_53_s800',
+            'fr.speech2text.whisper.small_defined_dot_ai_qc_french_combined_dataset_normalized': 'asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized',
             'fr.stopwords': 'stopwords_iso',
             'fr.stopwords.iso': 'stopwords_iso'},
         'fro': {'fro.lemma': 'lemma_srcmf',
@@ -7397,6 +7443,10 @@ class Spellbook:
                'hi.speech2text.wav2vec_xlsr.v2_large_300m_gpu_wx1.by_drishtisharma': 'asr_wav2vec2_large_xls_r_300m_wx1_gpu',
                'hi.speech2text.wav2vec_xlsr.v2_large_300m_wx1.by_drishtisharma': 'asr_wav2vec2_large_xls_r_300m_wx1',
                'hi.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_hindi_gpu',
+               'hi.speech2text.whisper.small_french_yocel1': 'asr_whisper_small_french_yocel1',
+               'hi.speech2text.whisper.small_hindi_norwegian_tensorboard': 'asr_whisper_small_hindi_norwegian_tensorboard',
+               'hi.speech2text.whisper.small_hindi_shripadbhat': 'asr_whisper_small_hindi_shripadbhat',
+               'hi.speech2text.whisper.small_hindi_xinhuang': 'asr_whisper_small_hindi_xinhuang',
                'hi.stopwords': 'stopwords_iso',
                'hi.stopwords.iso': 'stopwords_iso'},
         'hif': {'hif.embed.w2v_cc_300d': 'w2v_cc_300d'},
@@ -7438,6 +7488,7 @@ class Spellbook:
                'hy.lemma.armtdp': 'lemma_armtdp',
                'hy.pos': 'pos_ud_armtdp',
                'hy.pos.armtdp': 'pos_armtdp',
+               'hy.speech2text.whisper.small_armenian': 'asr_whisper_small_armenian',
                'hy.stopwords': 'stopwords_iso',
                'hy.stopwords.iso': 'stopwords_iso'},
         'hyw': {'hyw.lemma': 'lemma_armtdp', 'hyw.pos': 'pos_armtdp'},
@@ -7670,6 +7721,9 @@ class Spellbook:
                'it.speech2text.wav2vec_xlsr.v2_s237_exp': 'asr_exp_w2v2t_xlsr_53_s237',
                'it.speech2text.wav2vec_xlsr.v2_s387_exp': 'asr_exp_w2v2t_xlsr_53_s387',
                'it.speech2text.wav2vec_xlsr.v2_s417_exp': 'asr_exp_w2v2t_xls_r_s417',
+               'it.speech2text.whisper.small_italian_3': 'asr_whisper_small_italian_3',
+               'it.speech2text.whisper.tiny_italian_1': 'asr_whisper_tiny_italian_1',
+               'it.speech2text.whisper.tiny_italian_2': 'asr_whisper_tiny_italian_2',
                'it.stopwords': 'stopwords_iso',
                'it.stopwords.iso': 'stopwords_iso'},
         'ja': {
@@ -7740,6 +7794,8 @@ class Spellbook:
             'ja.pos.ud_gsd': 'pos_ud_gsd',
             'ja.segment_words': 'wordseg_gsd_ud',
             'ja.speech2text.wav2vec_xlsr.v2_large': 'asr_wav2vec2_large_xlsr_japanese_hiragana',
+            'ja.speech2text.whisper.small_japanese_jakeyoo': 'asr_whisper_small_japanese_jakeyoo',
+            'ja.speech2text.whisper.small_japanese_vumichien': 'asr_whisper_small_japanese_vumichien',
             'ja.stopwords': 'stopwords_iso',
             'ja.stopwords.iso': 'stopwords_iso'},
         'jv': {'jv.embed.bert.imdb_javanese.small': 'bert_embeddings_javanese_small_imdb',
@@ -7764,6 +7820,8 @@ class Spellbook:
                'kn.embed.KNUBert': 'roberta_embeddings_KNUBert',
                'kn.embed.KanBERTo': 'roberta_embeddings_KanBERTo',
                'kn.stopwords': 'stopwords_iso',
+               'kn.speech2text.whisper.kannada_base': 'asr_whisper_kannada_base',
+               'kn.speech2text.whisper.kannada_small': 'asr_whisper_kannada_small',
                'ml.detect_sentence': 'sentence_detector_dl'},
         'ko': {'ko.answer_question.bert': 'bert_qa_komrc_train',
                'ko.answer_question.bert.by_taekyoon': 'bert_qa_neg_komrc_train',
@@ -7846,6 +7904,7 @@ class Spellbook:
                'ko.segment_words': 'wordseg_kaist_ud',
                'ko.speech2text.wav2vec_xlsr.v2_large': 'asr_wav2vec2_large_xlsr_korean',
                'ko.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_korean_gpu',
+               'ko.speech2text.whisper.small_korean_fl': 'asr_whisper_small_korean_fl',
                'ko.stopwords': 'stopwords_iso'},
         'kr': {'kr.speech2text.wav2vec_xlsr.v2': 'asr_wav2vec2_xlsr_korean_senior',
                'kr.speech2text.wav2vec_xlsr.v2_gpu': 'asr_wav2vec2_xlsr_korean_senior_gpu'},
@@ -7917,6 +7976,8 @@ class Spellbook:
                'lt.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_53_lithuanian_by_deividasm_gpu',
                'lt.speech2text.wav2vec_xlsr.v2_large_gpu.by_dundar': 'asr_wav2vec2_large_xlsr_53_lithuanian_by_dundar_gpu',
                'lt.speech2text.wav2vec_xlsr.v2_large_gpu.by_m3hrdadfi': 'asr_wav2vec2_large_xlsr_lithuanian_gpu',
+               'lt.speech2text.whisper.lithuanian_finetune': 'asr_whisper_lithuanian_finetune',
+               'lt.speech2text.whisper.small_lithuanian_deividasm': 'asr_whisper_small_lithuanian_deividasm',
                'lt.stopwords': 'stopwords_iso'},
         'lu': {'lu.embed.bert.medium': 'bert_embeddings_medium_luxembourgish'},
         'luo': {
@@ -7950,6 +8011,7 @@ class Spellbook:
                'ml.classify.xlmr_roberta': 'xlmroberta_classifier_deoffxlmr_mono_malyalam',
                'ml.detect_sentence': 'sentence_detector_dl',
                'ml.embed.w2v_cc_300d': 'w2v_cc_300d',
+               'ml.speech2text.whisper.malayalam_first_model': 'asr_whisper_malayalam_first_model',
                'ml.stopwords': 'stopwords_iso'},
         'mn': {'mn.embed.w2v_cc_300d': 'w2v_cc_300d',
                'mn.ner.roberta.base': 'roberta_ner_roberta_base_ner',
@@ -7960,7 +8022,8 @@ class Spellbook:
                'mn.speech2text.wav2vec_xlsr.v2_large.by_manandey': 'asr_wav2vec2_large_xlsr_mongolian_by_manandey',
                'mn.speech2text.wav2vec_xlsr.v2_large.by_tugstugi': 'asr_wav2vec2_large_xlsr_53_mongolian_by_tugstugi',
                'mn.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_53_mongolian_by_tugstugi_gpu',
-               'mn.speech2text.wav2vec_xlsr.v2_large_gpu.by_manandey': 'asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu'},
+               'mn.speech2text.wav2vec_xlsr.v2_large_gpu.by_manandey': 'asr_wav2vec2_large_xlsr_mongolian_by_manandey_gpu',
+               'mn.speech2text.whisper.small_mongolian_1': 'asr_whisper_small_mongolian_1'},
         'mr': {'mr.detect_sentence': 'sentence_detector_dl',
                'mr.embed.albert': 'albert_embeddings_marathi_albert',
                'mr.embed.albert_v2': 'albert_embeddings_marathi_albert_v2',
@@ -8003,6 +8066,7 @@ class Spellbook:
         'nds': {'nds.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'ne': {'ne.detect_sentence': 'sentence_detector_dl',
                'ne.embed.w2v_cc_300d': 'w2v_cc_300d',
+               'ne.speech2text.whisper.small_nepali_np': 'asr_whisper_small_nepali_np',
                'ne.stopwords': 'stopwords_iso'},
         'new': {'new.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'nl': {
@@ -8122,6 +8186,7 @@ class Spellbook:
             'nl.speech2text.wav2vec_xlsr.v2_s799_exp': 'asr_exp_w2v2t_xlsr_53_s799',
             'nl.speech2text.wav2vec_xlsr.v2_s948_exp': 'asr_exp_w2v2t_xlsr_53_s948',
             'nl.speech2text.wav2vec_xlsr.v2_s972_exp': 'asr_exp_w2v2t_xlsr_53_s972',
+            'nl.speech2text.whisper.small_dutch': 'asr_whisper_small_dutch',
             'nl.stopwords': 'stopwords_iso'},
         'nn': {'nn.embed.w2v_cc_300d': 'w2v_cc_300d',
                'nn.pos': 'pos_ud_nynorsk',
@@ -8142,7 +8207,8 @@ class Spellbook:
                'no.pos': 'pos_bokmaal',
                'no.pos.bokmaal': 'pos_bokmaal',
                'no.pos.nynorsk': 'pos_nynorsk',
-               'no.pos.nynorsklia': 'pos_nynorsklia'},
+               'no.pos.nynorsklia': 'pos_nynorsklia',
+               'no.speech2text.whisper.small_nob': 'asr_whisper_small_nob'},
         'nso': {'nso.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'oc': {'oc.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'or': {'or.embed.w2v_cc_300d': 'w2v_cc_300d'},
@@ -8154,7 +8220,8 @@ class Spellbook:
         'os': {'os.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'pa': {'pa.detect_sentence': 'sentence_detector_dl',
                'pa.embed.muril_adapted_local': 'bert_embeddings_muril_adapted_local',
-               'pa.embed.w2v_cc_300d': 'w2v_cc_300d'},
+               'pa.embed.w2v_cc_300d': 'w2v_cc_300d',
+               'pa.speech2text.whisper.small_punjabi_eastern': 'asr_whisper_small_punjabi_eastern'},
         'pcm': {'pcm.embed.xlm_roberta': 'xlm_roberta_base_finetuned_naija',
                 'pcm.embed_sentence.xlm_roberta': 'sent_xlm_roberta_base_finetuned_naija',
                 'pcm.lemma.nsc': 'lemma_nsc',
@@ -8187,10 +8254,13 @@ class Spellbook:
             'pl.pos.pdb': 'pos_pdb',
             'pl.pos.ud_lfg': 'pos_ud_lfg',
             'pl.stopwords': 'stopwords_iso',
-            'pl.stopwords.iso': 'stopwords_iso'},
+            'pl.stopwords.iso': 'stopwords_iso',
+            'pl.speech2text.whisper.small_polish_aspik101': 'asr_whisper_small_polish_aspik101',
+            'pl.speech2text.whisper.tiny_polish': 'asr_whisper_tiny_polish'},
         'pms': {'pms.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'pnb': {'pnb.embed.w2v_cc_300d': 'w2v_cc_300d'},
-        'ps': {'ps.embed.w2v_cc_300d': 'w2v_cc_300d'},
+        'ps': {'ps.embed.w2v_cc_300d': 'w2v_cc_300d',
+               'ps.speech2text.whisper.small_pashto_ihanif': 'asr_whisper_small_pashto_ihanif'},
         'pt': {
             'pt.answer_question.distil_bert.squad.finetuned': 'distilbert_qa_finetuned_squad',
             'pt.answer_question.squad.bert.base_cased': 'bert_qa_bert_base_portuguese_cased_finetuned_squad_v1_pt_mrm8488',
@@ -8534,6 +8604,9 @@ class Spellbook:
             'sv.speech2text.wav2vec_xlsr.v2_large.by_marma': 'asr_wav2vec2_large_xlsr_swedish',
             'sv.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_welsh_gpu',
             'sv.speech2text.wav2vec_xlsr.v2_large_gpu.by_marma': 'asr_wav2vec2_large_xlsr_swedish_gpu',
+            'sv.speech2text.whisper.small_swedish_english': 'asr_whisper_small_swedish_english',
+            'sv.speech2text.whisper.small_swedish_test_3000': 'asr_whisper_small_swedish_test_3000',
+            'sv.speech2text.whisper.small_swedish_torileatherman': 'asr_whisper_small_swedish_torileatherman',
             'sv.stopwords': 'stopwords_iso',
             'sv.stopwords.iso': 'stopwords_iso'},
         'sw': {
@@ -8556,6 +8629,7 @@ class Spellbook:
             'sw.ner.xlmr_roberta.base_finetuned_swahili.v2.by_mbeukman': 'xlmroberta_ner_base_finetuned_swahili_finetuned_ner_swahili',
             'sw.ner.xlmr_roberta.base_finetuned_wolof.by_mbeukman': 'xlmroberta_ner_base_finetuned_wolof_finetuned_ner_swahili',
             'sw.ner.xlmr_roberta.base_finetuned_yoruba.by_mbeukman': 'xlmroberta_ner_base_finetuned_yoruba_finetuned_ner_swahili',
+            'sw.speech2text.whisper.small_swahili_pplantinga': 'asr_whisper_small_swahili_pplantinga',
             'sw.stopwords': 'stopwords_sw'},
         'swa': {'swa.ner.bert.uncased_base': 'bert_ner_mbert_base_uncased_ner_swa',
                 'swa.ner.bert.uncased_base.by_arnolfokam': 'bert_ner_mbert_base_uncased_swa',
@@ -8570,6 +8644,7 @@ class Spellbook:
             'ta.lemma': 'lemma',
             'ta.lemma.ttb': 'lemma_ttb',
             'ta.pos': 'pos_ttb',
+            'ta.speech2text.whisper.tiny_tamil_example': 'asr_whisper_tiny_tamil_example',
             'ta.stopwords': 'stopwords_iso'},
         'te': {'te.detect_sentence': 'sentence_detector_dl',
                'te.embed.bert': 'bert_embeddings_indic_transformers',
@@ -8584,6 +8659,8 @@ class Spellbook:
                'te.embed.xlmr_roberta': 'xlmroberta_embeddings_indic_transformers_te_xlmroberta',
                'te.lemma': 'lemma_mtg',
                'te.pos': 'pos_mtg',
+               'te.speech2text.whisper.small_telugu_146h': 'asr_whisper_small_telugu_146h',
+               'te.speech2text.whisper.telugu_tiny': 'asr_whisper_telugu_tiny',
                'te.stopwords': 'stopwords_iso'},
         'tg': {'tg.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'th': {
@@ -8600,6 +8677,7 @@ class Spellbook:
             'th.pos': 'pos_lst20',
             'th.segment_words': 'wordseg_best',
             'th.sentiment': 'sentiment_jager_use',
+            'th.speech2text.whisper.small_thai_napatswift': 'asr_whisper_small_thai_napatswift',
             'th.stopwords': 'stopwords_iso',
             'th.stopwords.iso': 'stopwords_iso'},
         'ti': {'ti.classify.roberta': 'roberta_classifier_ti_geezswitch',
@@ -8724,6 +8802,7 @@ class Spellbook:
                'tt.speech2text.wav2vec_xlsr.v2_large_gpu': 'asr_wav2vec2_large_xlsr_53_tatar_by_crang_gpu',
                'tt.speech2text.wav2vec_xlsr.v2_large_small': 'asr_wav2vec2_large_xlsr_53_W2V2_TATAR_SMALL',
                'tt.speech2text.wav2vec_xlsr.v2_large_small_gpu': 'asr_wav2vec2_large_xlsr_53_w2v2_tatar_small_gpu',
+               'tt.speech2text.whisper.small_tatar': 'asr_whisper_small_tatar',
                'tt.stopwords': 'stopwords_iso'},
         'tw': {'tw.speech2text.wav2vec_xlsr.v2': 'asr_wav2vec2large_xlsr_akan'},
         'ug': {'ug.embed.w2v_cc_300d': 'w2v_cc_300d',
@@ -8746,6 +8825,7 @@ class Spellbook:
                'uk.pos.bert_large_slavic_cyrillic_upos': 'bert_pos_bert_large_slavic_cyrillic_upos',
                'uk.pos.iu': 'pos_iu',
                'uk.pos.ud_iu': 'pos_ud_iu',
+               'uk.speech2text.whisper.small_ukrainian': 'asr_whisper_small_ukrainian',
                'uk.stopwords': 'stopwords_iso'},
         'unk': {
             'unk.ner.bert': 'bert_token_classifier_autotrain_medicaltokenclassification_1279048948'},
@@ -8776,7 +8856,8 @@ class Spellbook:
         'uz': {'uz.classify.bert.news.': 'bert_classifier_uzbek_news_category',
                'uz.embed.w2v_cc_300d': 'w2v_cc_300d',
                'uz.speech2text.wav2vec2': 'asr_uzbek_stt',
-               'uz.speech2text.wav2vec2.gpu': 'asr_uzbek_stt_gpu'},
+               'uz.speech2text.wav2vec2.gpu': 'asr_uzbek_stt_gpu',
+               'uz.speech2text.whisper.small_uzbek': 'asr_whisper_small_uzbek'},
         'vec': {'vec.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'vi': {'vi.answer_question.bert': 'bert_qa_bert_qa_vi_nvkha',
                'vi.answer_question.bert.cased_multilingual_base': 'bert_qa_multilingual_bert_base_cased_vietnamese',
@@ -8807,6 +8888,7 @@ class Spellbook:
                'vi.speech2text.wav2vec_xlsr.v2_large_gpu.by_cuongld': 'asr_wav2vec2_large_xlsr_vietnamese_by_cuongld_gpu',
                'vi.speech2text.wav2vec_xlsr.v2_large_gpu.by_nhut': 'asr_wav2vec2_large_xlsr_vietnamese_by_nhut_gpu',
                'vi.speech2text.wav2vec_xlsr.v2_large_gpu.by_not_tanh': 'asr_wav2vec2_large_xlsr_53_vietnamese_by_not_tanh_gpu',
+               'vi.speech2text.whisper.small_vietnamese_tuananh7198': 'asr_whisper_small_vietnamese_tuananh7198',
                'vi.stopwords': 'stopwords_iso'},
         'vls': {'vls.embed.w2v_cc_300d': 'w2v_cc_300d'},
         'vn': {
@@ -10165,6 +10247,11 @@ class Spellbook:
                'xx.swc.marian.translate_to.fi': 'opus_mt_fi_swc',
                'xx.swc.marian.translate_to.fr': 'opus_mt_fr_swc',
                'xx.swc.marian.translate_to.sv': 'opus_mt_sv_swc',
+               'xx.speech2text.whisper.base': 'asr_whisper_base',
+               'xx.speech2text.whisper.base_bengali_trans': 'asr_whisper_base_bengali_trans',
+               'xx.speech2text.whisper.small': 'asr_whisper_small',
+               'xx.speech2text.whisper.tiny': 'asr_whisper_tiny',
+               'xx.speech2text.whisper.tiny_opt': 'asr_whisper_tiny_opt',
                'xx.taw.marian.translate_to.en': 'opus_mt_taw_en',
                'xx.th.marian.translate_to.en': 'opus_mt_th_en',
                'xx.th.marian.translate_to.sv': 'opus_mt_sv_th',
@@ -10490,6 +10577,8 @@ class Spellbook:
                'zh.segment_words.pku': 'wordseg_pku',
                'zh.segment_words.weibo': 'wordseg_weibo',
                'zh.stopwords': 'stopwords_iso',
+               'zh.speech2text.whisper.small_chinese': 'asr_whisper_small_chinese',
+               'zh.speech2text.whisper.small_chinesebasetw': 'asr_whisper_small_chinesebasetw',
                'zh.tokenize': 'wordseg_weibo'},
         'zu': {'zu.embed.roberta': 'roberta_embeddings_zuberta',
                'zu.stopwords': 'stopwords_zu'}}
@@ -12568,6 +12657,95 @@ class Spellbook:
                              'asr_xlsr_wav2vec2_final_gpu': 'Wav2Vec2ForCTC',
                              'asr_xlsr_wav2vec_english': 'Wav2Vec2ForCTC',
                              'asr_xlsr_wav2vec_english_gpu': 'Wav2Vec2ForCTC',
+                             'asr_personal_whisper_small_english_model': 'WhisperForCTC',
+                             'asr_whisper_base': 'WhisperForCTC',
+                             'asr_whisper_base_bengali_trans': 'WhisperForCTC',
+                             'asr_whisper_base_bulgarian_l': 'WhisperForCTC',
+                             'asr_whisper_base_english': 'WhisperForCTC',
+                             'asr_whisper_base_european': 'WhisperForCTC',
+                             'asr_whisper_base_swedish': 'WhisperForCTC',
+                             'asr_whisper_danish_small_augmented': 'WhisperForCTC',
+                             'asr_whisper_kannada_base': 'WhisperForCTC',
+                             'asr_whisper_kannada_small': 'WhisperForCTC',
+                             'asr_whisper_lithuanian_finetune': 'WhisperForCTC',
+                             'asr_whisper_malayalam_first_model': 'WhisperForCTC',
+                             'asr_whisper_persian_farsi': 'WhisperForCTC',
+                             'asr_whisper_samoan_farsipal_e5': 'WhisperForCTC',
+                             'asr_whisper_small': 'WhisperForCTC',
+                             'asr_whisper_small_allsnr': 'WhisperForCTC',
+                             'asr_whisper_small_arabic_cv11': 'WhisperForCTC',
+                             'asr_whisper_small_armenian': 'WhisperForCTC',
+                             'asr_whisper_small_bak': 'WhisperForCTC',
+                             'asr_whisper_small_bengali_subhadeep': 'WhisperForCTC',
+                             'asr_whisper_small_chinese': 'WhisperForCTC',
+                             'asr_whisper_small_chinese_hk': 'WhisperForCTC',
+                             'asr_whisper_small_chinese_tw_voidful': 'WhisperForCTC',
+                             'asr_whisper_small_chinesebasetw': 'WhisperForCTC',
+                             'asr_whisper_small_czech_cv11': 'WhisperForCTC',
+                             'asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized': 'WhisperForCTC',
+                             'asr_whisper_small_dutch': 'WhisperForCTC',
+                             'asr_whisper_small_english': 'WhisperForCTC',
+                             'asr_whisper_small_english_blueraccoon': 'WhisperForCTC',
+                             'asr_whisper_small_finnish_15k_samples': 'WhisperForCTC',
+                             'asr_whisper_small_finnish_sgangireddy': 'WhisperForCTC',
+                             'asr_whisper_small_french_yocel1': 'WhisperForCTC',
+                             'asr_whisper_small_german': 'WhisperForCTC',
+                             'asr_whisper_small_greek': 'WhisperForCTC',
+                             'asr_whisper_small_hindi_norwegian_tensorboard': 'WhisperForCTC',
+                             'asr_whisper_small_hindi_shripadbhat': 'WhisperForCTC',
+                             'asr_whisper_small_hindi_xinhuang': 'WhisperForCTC',
+                             'asr_whisper_small_hungarian_cv11': 'WhisperForCTC',
+                             'asr_whisper_small_italian_3': 'WhisperForCTC',
+                             'asr_whisper_small_japanese_jakeyoo': 'WhisperForCTC',
+                             'asr_whisper_small_japanese_vumichien': 'WhisperForCTC',
+                             'asr_whisper_small_korean_fl': 'WhisperForCTC',
+                             'asr_whisper_small_lithuanian_deividasm': 'WhisperForCTC',
+                             'asr_whisper_small_lithuanian_serbian_v2': 'WhisperForCTC',
+                             'asr_whisper_small_mongolian_1': 'WhisperForCTC',
+                             'asr_whisper_small_mongolian_2': 'WhisperForCTC',
+                             'asr_whisper_small_mongolian_3': 'WhisperForCTC',
+                             'asr_whisper_small_nepali_np': 'WhisperForCTC',
+                             'asr_whisper_small_nob': 'WhisperForCTC',
+                             'asr_whisper_small_pashto_ihanif': 'WhisperForCTC',
+                             'asr_whisper_small_polish_aspik101': 'WhisperForCTC',
+                             'asr_whisper_small_portuguese_yapeng': 'WhisperForCTC',
+                             'asr_whisper_small_punjabi_eastern': 'WhisperForCTC',
+                             'asr_whisper_small_se2': 'WhisperForCTC',
+                             'asr_whisper_small_spanish_1e_6': 'WhisperForCTC',
+                             'asr_whisper_small_spanish_ari': 'WhisperForCTC',
+                             'asr_whisper_small_swahili_pplantinga': 'WhisperForCTC',
+                             'asr_whisper_small_swe2': 'WhisperForCTC',
+                             'asr_whisper_small_swe_davidt123': 'WhisperForCTC',
+                             'asr_whisper_small_swedish_english': 'WhisperForCTC',
+                             'asr_whisper_small_swedish_se_afroanton': 'WhisperForCTC',
+                             'asr_whisper_small_swedish_test_3000': 'WhisperForCTC',
+                             'asr_whisper_small_swedish_torileatherman': 'WhisperForCTC',
+                             'asr_whisper_small_tatar': 'WhisperForCTC',
+                             'asr_whisper_small_telugu_146h': 'WhisperForCTC',
+                             'asr_whisper_small_telugu_openslr': 'WhisperForCTC',
+                             'asr_whisper_small_thai_napatswift': 'WhisperForCTC',
+                             'asr_whisper_small_tonga_zambia': 'WhisperForCTC',
+                             'asr_whisper_small_ukrainian': 'WhisperForCTC',
+                             'asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic': 'WhisperForCTC',
+                             'asr_whisper_small_uzbek': 'WhisperForCTC',
+                             'asr_whisper_small_vietnamese_tuananh7198': 'WhisperForCTC',
+                             'asr_whisper_telugu_tiny': 'WhisperForCTC',
+                             'asr_whisper_testrun1': 'WhisperForCTC',
+                             'asr_whisper_tiny': 'WhisperForCTC',
+                             'asr_whisper_tiny_bulgarian_l': 'WhisperForCTC',
+                             'asr_whisper_tiny_english': 'WhisperForCTC',
+                             'asr_whisper_tiny_european': 'WhisperForCTC',
+                             'asr_whisper_tiny_german': 'WhisperForCTC',
+                             'asr_whisper_tiny_italian_1': 'WhisperForCTC',
+                             'asr_whisper_tiny_italian_2': 'WhisperForCTC',
+                             'asr_whisper_tiny_italian_local': 'WhisperForCTC',
+                             'asr_whisper_tiny_opt': 'WhisperForCTC',
+                             'asr_whisper_tiny_pashto': 'WhisperForCTC',
+                             'asr_whisper_tiny_polish': 'WhisperForCTC',
+                             'asr_whisper_tiny_spanish_arpagon': 'WhisperForCTC',
+                             'asr_whisper_tiny_tamil_example': 'WhisperForCTC',
+                             'asr_whisper_tiny_tgl': 'WhisperForCTC',
+                             'asr_whisper_tswana_greek_modern_e1': 'WhisperForCTC',
                              'assertion_dl': 'AssertionDLModel',
                              'assertion_dl_biobert': 'AssertionDLModel',
                              'assertion_dl_biobert_scope_L10R10': 'AssertionDLModel',
diff --git a/nlu/universe/annotator_class_universe.py b/nlu/universe/annotator_class_universe.py
index 20e0b564..33657efc 100644
--- a/nlu/universe/annotator_class_universe.py
+++ b/nlu/universe/annotator_class_universe.py
@@ -17,6 +17,7 @@ class AnnoClassRef:
         A_N.E5_SENTENCE_EMBEDDINGS: 'E5Embeddings',
         A_N.INSTRUCTOR_SENTENCE_EMBEDDINGS:'InstructorEmbeddings',
 
+        A_N.WHISPER_FOR_CTC: 'WhisperForCTC',
         A_N.HUBERT_FOR_CTC: 'HubertForCTC',
         A_N.CAMEMBERT_FOR_QUESTION_ANSWERING: 'CamemBertForQuestionAnswering',
         A_N.SWIN_IMAGE_CLASSIFICATION: 'SwinForImageClassification',
diff --git a/nlu/universe/component_universes.py b/nlu/universe/component_universes.py
index 6c0ba566..9ff36da9 100644
--- a/nlu/universe/component_universes.py
+++ b/nlu/universe/component_universes.py
@@ -8,6 +8,7 @@
 from nlu.components.chunkers.ngram.ngram import NGram
 from nlu.components.classifiers.asr.wav2Vec import Wav2Vec
 from nlu.components.classifiers.asr_hubert.hubert import Hubert
+from nlu.components.classifiers.asr_whisper.whisper import Whisper
 from nlu.components.classifiers.bert_zero_shot_classification.bert_zero_shot import BertZeroShotClassifier
 from nlu.components.classifiers.classifier_dl.classifier_dl import ClassifierDl
 from nlu.components.classifiers.distil_bert_zero_shot_classification.distil_bert_zero_shot import \
@@ -1481,6 +1482,27 @@ class ComponentUniverse:
                                   applicable_file_types=['wav', 'mp3', 'flac', 'aiff', 'aifc', 'ogg', 'aflac', 'alac',
                                                          'dsd', 'pcm', ]
                                   ),
+        A.WHISPER_FOR_CTC: partial(NluComponent,
+                                   name=A.WHISPER_FOR_CTC,
+                                   type=T.SPEECH_RECOGNIZER,
+                                   get_default_model=Whisper.get_default_model,
+                                   get_pretrained_model=Whisper.get_pretrained_model,
+                                   pdf_extractor_methods={'default': default_only_result_config,
+                                                          'default_full': default_full_config, },
+                                   pdf_col_name_substitutor=substitute_wav2vec_cols,
+                                   output_level=L.DOCUMENT,
+                                   node=NLP_FEATURE_NODES.nodes[A.WHISPER_FOR_CTC],
+                                   description='Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. It transcribe in multiple languages, as well as translate from those languages into English.',
+                                   provider=ComponentBackends.open_source,
+                                   license=Licenses.open_source,
+                                   computation_context=ComputeContexts.spark,
+                                   output_context=ComputeContexts.spark,
+                                   jsl_anno_class_id=A.WHISPER_FOR_CTC,
+                                   jsl_anno_py_class=ACR.JSL_anno2_py_class[A.WHISPER_FOR_CTC],
+                                   # Bas on Librosa which uses http://www.mega-nerd.com/libsndfile/
+                                   applicable_file_types=['wav', 'mp3', 'flac', 'aiff', 'aifc', 'ogg', 'aflac', 'alac',
+                                                          'dsd', 'pcm', ]
+                                   ),
 
         A.TAPAS_FOR_QA: partial(NluComponent,
                                 name=A.TAPAS_FOR_QA,
diff --git a/nlu/universe/feature_node_ids.py b/nlu/universe/feature_node_ids.py
index bbcaa12e..39edaf9c 100644
--- a/nlu/universe/feature_node_ids.py
+++ b/nlu/universe/feature_node_ids.py
@@ -27,6 +27,7 @@ class NLP_NODE_IDS:
     AUDIO_ASSEMBLER = JslAnnoId('audio_assembler')
     WAV2VEC_FOR_CTC = JslAnnoId('wav2vec_for_ctc')
     HUBERT_FOR_CTC = JslAnnoId('hubert_for_ctc')
+    WHISPER_FOR_CTC = JslAnnoId('whisper_for_ctc')
     TABLE_ASSEMBLER = JslAnnoId('table_assembler')
     TAPAS_FOR_QA = JslAnnoId('tapas')
     MULTI_DOCUMENT_ASSEMBLER = JslAnnoId('multi_document_assembler')
diff --git a/nlu/universe/feature_node_universes.py b/nlu/universe/feature_node_universes.py
index fe0f6dec..653f76a7 100644
--- a/nlu/universe/feature_node_universes.py
+++ b/nlu/universe/feature_node_universes.py
@@ -135,6 +135,7 @@ class NLP_FEATURE_NODES:  # or Mode Node?
         # A.WAV2VEC_FOR_CTC: NlpFeatureNode(A.PARTIALLY_IMPLEMENTED, [F.AUDIO], [F.RECOGNIZED_SPEECH_TEXT]),
         A.WAV2VEC_FOR_CTC: NlpFeatureNode(A.WAV2VEC_FOR_CTC, [F.AUDIO], [E.RAW_TEXT]),
         A.HUBERT_FOR_CTC: NlpFeatureNode(A.HUBERT_FOR_CTC, [F.AUDIO], [E.RAW_TEXT]),
+        A.WHISPER_FOR_CTC: NlpFeatureNode(A.WHISPER_FOR_CTC, [F.AUDIO], [E.RAW_TEXT]),
 
         A.IMAGE_ASSEMBLER: NlpFeatureNode(A.IMAGE_ASSEMBLER, [F.SPARK_NLP_IMAGE, F.SPARK_NLP_FILE_PATH], [F.IMAGE]),
         A.DOCUMENT_NORMALIZER: NlpFeatureNode(A.DOCUMENT_NORMALIZER, [F.DOCUMENT], [F.DOCUMENT_GENERATED]),
diff --git a/tests/nlu_core_tests/component_tests/classifier_tests/asr_tests.py b/tests/nlu_core_tests/component_tests/classifier_tests/asr_tests.py
index 92c46976..b11cd53f 100644
--- a/tests/nlu_core_tests/component_tests/classifier_tests/asr_tests.py
+++ b/tests/nlu_core_tests/component_tests/classifier_tests/asr_tests.py
@@ -1,29 +1,16 @@
 import unittest
-import sparknlp
-import librosa as librosa
-from sparknlp.base import *
-from sparknlp.annotator import *
-import pandas as pd
-import pyspark.sql.functions as F
-from pyspark.sql.types import *
-import pyspark.sql.functions as F
-import sparknlp
-import sparknlp
-from pyspark.ml import Pipeline
-from sparknlp.annotator import *
-from sparknlp.base import *
 import os
 
 
-os.environ['PYSPARK_PYTHON'] = '/home/ckl/anaconda3/bin/python3'
-os.environ['PYSPARK_DRIVER_PYTHON'] = '/home/ckl/anaconda3/bin/python3'
+#os.environ['PYSPARK_PYTHON'] = '/home/ckl/anaconda3/bin/python3'
+#os.environ['PYSPARK_DRIVER_PYTHON'] = '/home/ckl/anaconda3/bin/python3'
 
 
 
 class AsrTestCase(unittest.TestCase):
     def test_wav2vec(self):
         import nlu
-        p = nlu.load('en.wav2vec.wip',verbose=True)
+        p = nlu.load('en.speech2text.wav2vec2.v2_base_960h',verbose=True)
         FILE_PATH = os.path.normpath(r"tests/datasets/audio/asr/ngm_12484_01067234848.wav")
 
         print("Got p ",p)
@@ -35,7 +22,17 @@ def test_wav2vec(self):
 
     def test_hubert(self):
         import nlu
-        p = nlu.load('en.asr_hubert_large_ls960',verbose=True)
+        p = nlu.load('en.speech2text.hubert.large_ls960',verbose=True)
+        FILE_PATH = os.path.normpath(r"tests/datasets/audio/asr/ngm_12484_01067234848.wav")
+
+        print("Got p ",p)
+        df = p.predict(FILE_PATH)
+        print(df)
+        df = p.predict([FILE_PATH,FILE_PATH])
+        print(df)
+    def test_whisper(self):
+        import nlu
+        p = nlu.load('xx.speech2text.whisper.tiny',verbose=True)
         FILE_PATH = os.path.normpath(r"tests/datasets/audio/asr/ngm_12484_01067234848.wav")
 
         print("Got p ",p)