{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# ADAPTING THE ADAPTERS FOR CODE-SWITCHING IN MULTILINGUAL ASR"
      ],
      "metadata": {
        "id": "d8Xbx-NnPRb5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Clone the repo\n"
      ],
      "metadata": {
        "id": "8YyJ22u_GvHL"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wkX5HmEcM9fm",
        "outputId": "c1022ab5-c638-45a4-9a3f-deef589310c6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'MMS-Code-Switching'...\n",
            "remote: Enumerating objects: 3819, done.\u001b[K\n",
            "remote: Counting objects: 100% (3819/3819), done.\u001b[K\n",
            "remote: Compressing objects: 100% (2739/2739), done.\u001b[K\n",
            "remote: Total 3819 (delta 1030), reused 3816 (delta 1027), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (3819/3819), 25.59 MiB | 21.63 MiB/s, done.\n",
            "Resolving deltas: 100% (1030/1030), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/Atharva7K/MMS-Code-Switching.git"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install modified transformers code"
      ],
      "metadata": {
        "id": "FXUijlVFGzcE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/MMS-Code-Switching/transformers\n",
        "%pip install -e ."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y8Frf-UJPEMA",
        "outputId": "79bb8dec-dd0b-47e6-c6fa-175e5dfb2668"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/MMS-Code-Switching/transformers\n",
            "Obtaining file:///content/MMS-Code-Switching/transformers\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Checking if build backend supports build_editable ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build editable ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing editable metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.32.0.dev0) (3.12.2)\n",
            "Collecting huggingface-hub<1.0,>=0.14.1 (from transformers==4.32.0.dev0)\n",
            "  Downloading huggingface_hub-0.17.2-py3-none-any.whl (294 kB)\n",
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            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.32.0.dev0) (1.23.5)\n",
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            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.32.0.dev0) (6.0.1)\n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers==4.32.0.dev0)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers==4.32.0.dev0)\n",
            "  Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers==4.32.0.dev0) (4.66.1)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers==4.32.0.dev0) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.14.1->transformers==4.32.0.dev0) (4.5.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.32.0.dev0) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.32.0.dev0) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.32.0.dev0) (2.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.32.0.dev0) (2023.7.22)\n",
            "Building wheels for collected packages: transformers\n",
            "  Building editable for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for transformers: filename=transformers-4.32.0.dev0-0.editable-py3-none-any.whl size=37394 sha256=210e0a90432f70f6a3c8109a0b080f164da9ae18f76943a9cabdbce401f893ea\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-f6ao8vw8/wheels/f0/96/a2/a4b90b4ff787d05e44e338fda6a4d3056126e50df2d8f9b60e\n",
            "Successfully built transformers\n",
            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.17.2 safetensors-0.3.3 tokenizers-0.13.3 transformers-4.32.0.dev0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Install other dependancies"
      ],
      "metadata": {
        "id": "5i5LSpyhG61L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/MMS-Code-Switching/\n",
        "%pip install -r requirements.txt"
      ],
      "metadata": {
        "id": "qlWioBLqNB2M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "16cff193-c3de-494c-840d-5e7e1daf3bd8"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/MMS-Code-Switching\n",
            "Collecting accelerate==0.20.3 (from -r requirements.txt (line 1))\n",
            "  Downloading accelerate-0.20.3-py3-none-any.whl (227 kB)\n",
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            "  Downloading evaluate-0.4.0-py3-none-any.whl (81 kB)\n",
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            "Installing collected packages: safetensors, xxhash, tzdata, rapidfuzz, numpy, llvmlite, dill, responses, pooch, pandas, numba, multiprocess, jiwer, scikit-learn, librosa, datasets, evaluate, accelerate\n",
            "  Attempting uninstall: safetensors\n",
            "    Found existing installation: safetensors 0.3.3\n",
            "    Uninstalling safetensors-0.3.3:\n",
            "      Successfully uninstalled safetensors-0.3.3\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.23.5\n",
            "    Uninstalling numpy-1.23.5:\n",
            "      Successfully uninstalled numpy-1.23.5\n",
            "  Attempting uninstall: llvmlite\n",
            "    Found existing installation: llvmlite 0.39.1\n",
            "    Uninstalling llvmlite-0.39.1:\n",
            "      Successfully uninstalled llvmlite-0.39.1\n",
            "  Attempting uninstall: pooch\n",
            "    Found existing installation: pooch 1.7.0\n",
            "    Uninstalling pooch-1.7.0:\n",
            "      Successfully uninstalled pooch-1.7.0\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 1.5.3\n",
            "    Uninstalling pandas-1.5.3:\n",
            "      Successfully uninstalled pandas-1.5.3\n",
            "  Attempting uninstall: numba\n",
            "    Found existing installation: numba 0.56.4\n",
            "    Uninstalling numba-0.56.4:\n",
            "      Successfully uninstalled numba-0.56.4\n",
            "  Attempting uninstall: scikit-learn\n",
            "    Found existing installation: scikit-learn 1.2.2\n",
            "    Uninstalling scikit-learn-1.2.2:\n",
            "      Successfully uninstalled scikit-learn-1.2.2\n",
            "  Attempting uninstall: librosa\n",
            "    Found existing installation: librosa 0.10.1\n",
            "    Uninstalling librosa-0.10.1:\n",
            "      Successfully uninstalled librosa-0.10.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires pandas==1.5.3, but you have pandas 2.0.3 which is incompatible.\n",
            "tensorflow 2.13.0 requires numpy<=1.24.3,>=1.22, but you have numpy 1.24.4 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed accelerate-0.20.3 datasets-2.14.4 dill-0.3.7 evaluate-0.4.0 jiwer-3.0.2 librosa-0.10.0.post2 llvmlite-0.40.1 multiprocess-0.70.15 numba-0.57.1 numpy-1.24.4 pandas-2.0.3 pooch-1.6.0 rapidfuzz-2.13.7 responses-0.18.0 safetensors-0.3.2 scikit-learn-1.3.0 tzdata-2023.3 xxhash-3.3.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gdown"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rvaPyzXiPU_5",
        "outputId": "f1698a7b-0af8-4935-cb6e-56512c8db350"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: gdown in /usr/local/lib/python3.10/dist-packages (4.6.6)\n",
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            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from gdown) (1.16.0)\n",
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            "Requirement already satisfied: PySocks!=1.5.7,>=1.5.6 in /usr/local/lib/python3.10/dist-packages (from requests[socks]->gdown) (1.7.1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Download MUCS Transformer Code Switcher checkpoint"
      ],
      "metadata": {
        "id": "kIB4NyCHHBSL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!gdown --fuzzy https://drive.google.com/file/d/1qs9cWSzNtFpA3Grqu_YoQl0c1uj1WvyI/view?usp=drive_link\n",
        "!mv /content/MMS-Code-Switching/pytorch_model.bin checkpoints/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iN_vuALhRNqG",
        "outputId": "9236837d-07d0-406e-95ae-4698dd7f11c0"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1qs9cWSzNtFpA3Grqu_YoQl0c1uj1WvyI\n",
            "To: /content/MMS-Code-Switching/pytorch_model.bin\n",
            "100% 3.92G/3.92G [00:45<00:00, 85.6MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "h2SYpiuyZABY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Use inference script to generate transcripts. We use 6 audio samples from MUCS validation set for this demo."
      ],
      "metadata": {
        "id": "oTI6cQIDHHNR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python inference.py --test_metadata_csv_path \"sample_audio_mucs/metadata.csv\" --target_lang_1 eng --target_lang_2 hin --prefix_path \"/content/MMS-Code-Switching/sample_audio_mucs/\" --checkpoint_path \"/content/MMS-Code-Switching/checkpoints/\"  --batch_size 32 --outfile_path \"output.csv\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ibphU4cbSR25",
        "outputId": "6088839f-b042-44bb-b701-a528605a8a42"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading Dependancies..\n",
            "2023-09-19 20:17:48.215252: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "Loading Model and Processor..\n",
            "num_proc must be <= 6. Reducing num_proc to 6 for dataset of size 6.\n",
            "Map (num_proc=6): 100% 6/6 [00:09<00:00,  1.64s/ examples]\n",
            "vocab size ===== 219\n",
            "Wav2Vec2ForCTCWithAdapterSwitching(\n",
            "  (wav2vec2): Wav2Vec2Model(\n",
            "    (feature_extractor): Wav2Vec2FeatureEncoder(\n",
            "      (conv_layers): ModuleList(\n",
            "        (0): Wav2Vec2LayerNormConvLayer(\n",
            "          (conv): Conv1d(1, 512, kernel_size=(10,), stride=(5,))\n",
            "          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
            "          (activation): GELUActivation()\n",
            "        )\n",
            "        (1-4): 4 x Wav2Vec2LayerNormConvLayer(\n",
            "          (conv): Conv1d(512, 512, kernel_size=(3,), stride=(2,))\n",
            "          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
            "          (activation): GELUActivation()\n",
            "        )\n",
            "        (5-6): 2 x Wav2Vec2LayerNormConvLayer(\n",
            "          (conv): Conv1d(512, 512, kernel_size=(2,), stride=(2,))\n",
            "          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
            "          (activation): GELUActivation()\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "    (feature_projection): Wav2Vec2FeatureProjection(\n",
            "      (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
            "      (projection): Linear(in_features=512, out_features=1280, bias=True)\n",
            "      (dropout): Dropout(p=0.0, inplace=False)\n",
            "    )\n",
            "    (encoder): Wav2Vec2EncoderStableLayerNorm(\n",
            "      (pos_conv_embed): Wav2Vec2PositionalConvEmbedding(\n",
            "        (conv): Conv1d(1280, 1280, kernel_size=(128,), stride=(1,), padding=(64,), groups=16)\n",
            "        (padding): Wav2Vec2SamePadLayer()\n",
            "        (activation): GELUActivation()\n",
            "      )\n",
            "      (layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "      (dropout): Dropout(p=0.0, inplace=False)\n",
            "      (code_switcher): TransformerCodeSwitcher(\n",
            "        (attention): Wav2Vec2Attention(\n",
            "          (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "          (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "          (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "          (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "        )\n",
            "        (dropout): Dropout(p=0.0, inplace=False)\n",
            "        (layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "        (feed_forward): CodeSwitcherFeedForward(\n",
            "          (sigmoid): Sigmoid()\n",
            "          (intermediate_dropout): Dropout(p=0.05, inplace=False)\n",
            "          (intermediate_dense): Linear(in_features=1280, out_features=5120, bias=True)\n",
            "          (intermediate_act_fn): GELUActivation()\n",
            "          (output_dense): Linear(in_features=5120, out_features=1, bias=True)\n",
            "        )\n",
            "        (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "      )\n",
            "      (layers): ModuleList(\n",
            "        (0-47): 48 x Wav2Vec2EncoderLayerStableLayerNormForCodeSwitching(\n",
            "          (attention): Wav2Vec2Attention(\n",
            "            (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "            (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "            (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "            (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
            "          )\n",
            "          (dropout): Dropout(p=0.0, inplace=False)\n",
            "          (layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "          (feed_forward): Wav2Vec2FeedForward(\n",
            "            (intermediate_dropout): Dropout(p=0.05, inplace=False)\n",
            "            (intermediate_dense): Linear(in_features=1280, out_features=5120, bias=True)\n",
            "            (intermediate_act_fn): GELUActivation()\n",
            "            (output_dense): Linear(in_features=5120, out_features=1280, bias=True)\n",
            "            (output_dropout): Dropout(p=0.0, inplace=False)\n",
            "          )\n",
            "          (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "          (adapter_layer_1): Wav2Vec2AttnAdapterLayer(\n",
            "            (norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "            (linear_1): Linear(in_features=1280, out_features=16, bias=True)\n",
            "            (act_fn): ReLU()\n",
            "            (linear_2): Linear(in_features=16, out_features=1280, bias=True)\n",
            "          )\n",
            "          (adapter_layer_2): Wav2Vec2AttnAdapterLayer(\n",
            "            (norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
            "            (linear_1): Linear(in_features=1280, out_features=16, bias=True)\n",
            "            (act_fn): ReLU()\n",
            "            (linear_2): Linear(in_features=16, out_features=1280, bias=True)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "    )\n",
            "  )\n",
            "  (dropout): Dropout(p=0.05, inplace=False)\n",
            "  (lm_head): Linear(in_features=1280, out_features=219, bias=True)\n",
            ")\n",
            "Setting up training..\n",
            "Staring evaluation..\n",
            "  0% 0/1 [00:00<?, ?it/s]Building prefix dict from the default dictionary ...\n",
            "Dumping model to file cache /tmp/jieba.cache\n",
            "Loading model cost 0.702 seconds.\n",
            "Prefix dict has been built successfully.\n",
            "{'mer': 0.36619718309859156, 'cer': 0.3207126948775056, 'wer_eval': 0.4411764705882353, 'cer_eval': 0.28807339449541286}\n",
            "100% 1/1 [00:00<00:00,  1.32it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "pd.read_csv('output.csv').head(6)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "9Nhno7AxGVNr",
        "outputId": "20250a79-984e-4221-b3fb-1147350a66c0"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Unnamed: 0                                          file_name  \\\n",
              "0           0  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "1           1  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "2           2  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "3           3  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "4           4  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "5           5  /content/MMS-Code-Switching/sample_audio_mucs/...   \n",
              "\n",
              "                                       transcription  \\\n",
              "0  लिबर ऑफिस impress में एक प्रस्तुति document बन...   \n",
              "1  इस tutorial में हम impress window के भागों के ...   \n",
              "2  यहाँ हम अपने ऑपरेटिंग सिस्टम के रूप में gnu/li...   \n",
              "3  चलिए अपनी प्रस्तुति प्रेजैटेशन sample impress ...   \n",
              "4           चलिए देखते हैं कि screen पर क्या क्या है   \n",
              "5  मध्य में हम खाली जगह देखते है जोकि workspace ह...   \n",
              "\n",
              "                             mms_model_transcription  \n",
              "0  liberoffice impress में एक परस्तुति document ब...  \n",
              "1  इस चीturl में हम impress वindoं के भागों के बा...  \n",
              "2  यहाँ हम अपने oprating सystem के रूप में genu l...  \n",
              "3  चलिए अपनी प्रसतुति sample impres oपn करते हैंज...  \n",
              "4          बनय चलिए देखते हैं कि sकren पर कया कया है  \n",
              "5  मध्य में हम खाली जगह देखते हैं जोकि work space...  "
            ],
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              "    <div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>file_name</th>\n",
              "      <th>transcription</th>\n",
              "      <th>mms_model_transcription</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>लिबर ऑफिस impress में एक प्रस्तुति document बन...</td>\n",
              "      <td>liberoffice impress में एक परस्तुति document ब...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>इस tutorial में हम impress window के भागों के ...</td>\n",
              "      <td>इस चीturl में हम impress वindoं के भागों के बा...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>यहाँ हम अपने ऑपरेटिंग सिस्टम के रूप में gnu/li...</td>\n",
              "      <td>यहाँ हम अपने oprating सystem के रूप में genu l...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>चलिए अपनी प्रस्तुति प्रेजैटेशन sample impress ...</td>\n",
              "      <td>चलिए अपनी प्रसतुति sample impres oपn करते हैंज...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>चलिए देखते हैं कि screen पर क्या क्या है</td>\n",
              "      <td>बनय चलिए देखते हैं कि sकren पर कया कया है</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5</td>\n",
              "      <td>/content/MMS-Code-Switching/sample_audio_mucs/...</td>\n",
              "      <td>मध्य में हम खाली जगह देखते है जोकि workspace ह...</td>\n",
              "      <td>मध्य में हम खाली जगह देखते हैं जोकि work space...</td>\n",
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              "    .colab-df-convert {\n",
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              "\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-6ce3b8f5-72f1-4603-a8d0-59a6a58072a6 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-6ce3b8f5-72f1-4603-a8d0-59a6a58072a6');\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",
              "\n",
              "<div id=\"df-fc5c8514-fcd0-4cc1-8593-90ebb7baff0e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fc5c8514-fcd0-4cc1-8593-90ebb7baff0e')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-fc5c8514-fcd0-4cc1-8593-90ebb7baff0e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    }
  ]
}