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| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/nguyenvulebinh/027930099445ae58523bd18137d7bc28/wav2vec2_vlsp_test.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "R6JZVJoWMs5z", | |
| "outputId": "6e1cd2b4-7bb0-484e-9541-a9a5bd952140" | |
| }, | |
| "source": [ | |
| "from google.colab import drive\n", | |
| "drive.mount('/content/drive')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Mounted at /content/drive\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "SRZxnzcxMag3" | |
| }, | |
| "source": [ | |
| "!pip3 install transformers==4.9.2 soundfile datasets==1.11.0 jiwer gpustat pyctcdecode pydub torchaudio auditok gradio onnxruntime\n", | |
| "!pip3 install https://github.com/kpu/kenlm/archive/master.zip\n", | |
| "!sudo apt-get install git-lfs nano htop\n", | |
| "!git lfs install" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Lt5p2A1SNaW_" | |
| }, | |
| "source": [ | |
| "from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor, Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor\n", | |
| "from datasets import load_from_disk, load_metric\n", | |
| "import torch\n", | |
| "import torchaudio\n", | |
| "import kenlm\n", | |
| "from pyctcdecode import Alphabet, BeamSearchDecoderCTC, LanguageModel\n", | |
| "import os\n", | |
| "import google\n", | |
| "from io import StringIO\n", | |
| "import base64" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 49, | |
| "referenced_widgets": [ | |
| "0d3b00b83c0040f9b165de8e8524a92b", | |
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| "outputId": "b688856f-3f17-48e4-a988-9764d02495c6" | |
| }, | |
| "source": [ | |
| "wer_metric = load_metric(\"wer\")" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "0d3b00b83c0040f9b165de8e8524a92b", | |
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| }, | |
| "text/plain": [ | |
| "Downloading: 0%| | 0.00/1.95k [00:00<?, ?B/s]" | |
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| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "zTJD4JPTM42j" | |
| }, | |
| "source": [ | |
| "def get_asr_model():\n", | |
| " pre_trained_path = '/content/vaw2tmp/model-bin/finetune/base/checkpoint-146596'\n", | |
| " tokenizer = Wav2Vec2CTCTokenizer(\"/content/vaw2tmp/model-bin/finetune/vocab.json\",\n", | |
| " unk_token=\"<unk>\",\n", | |
| " pad_token=\"<pad>\",\n", | |
| " word_delimiter_token=\"|\")\n", | |
| "\n", | |
| " feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(pre_trained_path)\n", | |
| " processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)\n", | |
| " # processor = Wav2Vec2Processor.from_pretrained(pre_trained_path)\n", | |
| "\n", | |
| " model = Wav2Vec2ForCTC.from_pretrained(\n", | |
| " pre_trained_path,\n", | |
| " gradient_checkpointing=True,\n", | |
| " ctc_loss_reduction=\"mean\",\n", | |
| " pad_token_id=processor.tokenizer.pad_token_id,\n", | |
| " )\n", | |
| "\n", | |
| " return tokenizer, processor, model" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "-77wwU-ftXuQ" | |
| }, | |
| "source": [ | |
| "def get_decoder_model(tokenizer):\n", | |
| " vocab_dict = tokenizer.get_vocab()\n", | |
| " sort_vocab = sorted((value, key) for (key, value) in vocab_dict.items())\n", | |
| " vocab = [x[1] for x in sort_vocab]\n", | |
| " vocab_list = vocab\n", | |
| " # convert ctc blank character representation\n", | |
| " vocab_list[tokenizer.pad_token_id] = \"\"\n", | |
| " # replace special characters\n", | |
| " vocab_list[tokenizer.unk_token_id] = \"\"\n", | |
| " # convert space character representation\n", | |
| " vocab_list[tokenizer.word_delimiter_token_id] = \" \"\n", | |
| " # specify ctc blank char index, since conventially it is the last entry of the logit matrix\n", | |
| " alphabet = Alphabet.build_alphabet(vocab_list, ctc_token_idx=tokenizer.pad_token_id)\n", | |
| "\n", | |
| " lm_model = kenlm.Model(\"/content/drive/MyDrive/audio_dataset/vi_lm_4grams.bin\")\n", | |
| "\n", | |
| " decoder = BeamSearchDecoderCTC(alphabet,\n", | |
| " language_model=LanguageModel(lm_model))\n", | |
| " return decoder" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "8wBZeJSPNxTp" | |
| }, | |
| "source": [ | |
| "w2v_tokenizer, w2v_processor, w2v_model = get_asr_model()\n", | |
| "w2v_ctc_decoder = get_decoder_model(w2v_tokenizer)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "B8E-gSlvRCKG" | |
| }, | |
| "source": [ | |
| "def map_to_result(batch):\n", | |
| " input_values = w2v_processor(\n", | |
| " batch[\"speech\"], \n", | |
| " sampling_rate=batch[\"sampling_rate\"], \n", | |
| " return_tensors=\"pt\"\n", | |
| " # ).input_values.to(\"cuda\")\n", | |
| " ).input_values\n", | |
| "\n", | |
| " if torch.cuda.is_available():\n", | |
| " w2v_model.to(\"cuda\")\n", | |
| " input_values = input_values.to(\"cuda\")\n", | |
| "\n", | |
| " with torch.no_grad():\n", | |
| " logits = w2v_model(input_values).logits\n", | |
| "\n", | |
| " pred_ids = torch.argmax(logits, dim=-1)\n", | |
| " batch[\"pred_str\"] = w2v_processor.batch_decode(pred_ids)[0]\n", | |
| " batch[\"pred_str_beam\"] = w2v_ctc_decoder.decode(logits[0].cpu().numpy(), beam_width=500)\n", | |
| "\n", | |
| " return batch" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "uTNny3CtkxYE" | |
| }, | |
| "source": [ | |
| "def speech_file_to_array_fn(path, max_seconds=-1):\n", | |
| " batch = {\"file\": path}\n", | |
| " speech_array, sampling_rate = torchaudio.load(batch[\"file\"])\n", | |
| " if sampling_rate != 16000:\n", | |
| " transform = torchaudio.transforms.Resample(orig_freq=sampling_rate,\n", | |
| " new_freq=16000)\n", | |
| " speech_array = transform(speech_array)\n", | |
| " speech_array = speech_array[0]\n", | |
| " if max_seconds > 0:\n", | |
| " speech_array = speech_array[:max_seconds*16000]\n", | |
| " batch[\"speech\"] = speech_array.numpy()\n", | |
| " batch[\"sampling_rate\"] = 16000\n", | |
| " return batch" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "O_uiqPPfN1z8" | |
| }, | |
| "source": [ | |
| "test_dataset_t1 = load_from_disk('/content/drive/MyDrive/audio_dataset/vlsp_test_dataset_t1')\n", | |
| "test_dataset_t1 = test_dataset_t1.filter(lambda example: len(example['speech']) < 160000,\n", | |
| " batch_size=32,\n", | |
| " num_proc=8,\n", | |
| " cache_file_name='/content/vaw2tmp/model-bin/metrics/cache-test.arrow')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "q4r3O4qwP03F" | |
| }, | |
| "source": [ | |
| "test_dataset_t2 = load_from_disk('/content/drive/MyDrive/audio_dataset/vlsp_test_dataset_t2')\n", | |
| "test_dataset_t2 = test_dataset_t2.filter(lambda example: len(example['speech']) < 160000,\n", | |
| " batch_size=32,\n", | |
| " num_proc=8,\n", | |
| " cache_file_name='/content/vaw2tmp/model-bin/metrics/cache-t2-test.arrow')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "8ijwjUtP_i-2" | |
| }, | |
| "source": [ | |
| "test_dataset_vivos = load_from_disk('/content/drive/MyDrive/audio_dataset/vivos_test_dataset')\n", | |
| "test_dataset_vivos = test_dataset_vivos.filter(lambda example: len(example['speech']) < 160000,\n", | |
| " batch_size=32,\n", | |
| " num_proc=8,\n", | |
| " cache_file_name='/content/vaw2tmp/model-bin/metrics/cache-vivos-test.arrow')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "33B2uqwo2r8m" | |
| }, | |
| "source": [ | |
| "test_dataset_common = load_from_disk('/content/drive/MyDrive/audio_dataset/common_voice_vi')\n", | |
| "test_dataset_common = test_dataset_common.filter(lambda example: len(example['speech']) < 160000,\n", | |
| " batch_size=32,\n", | |
| " num_proc=8,\n", | |
| " cache_file_name='/content/vaw2tmp/model-bin/metrics/cache-common-voice-test.arrow')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 83, | |
| "referenced_widgets": [ | |
| "1aff7fc4351345fbbdfe37841aa08f11", | |
| "0260a8e14e3c4090873dab8625ff7afd", | |
| "f2d215d18f6146e791eedf02452c668c", | |
| "e8e7ae7f753f4ef2b2517efec2db3387", | |
| "ec4f48f8ddbd426a92c713de53be12f1", | |
| "dbc86ff0937b42668565b893ca03a3c6", | |
| "972ed783418f4904be623be6c473e5f5", | |
| "658a16080a124e0da18bc49ce69be4b0", | |
| "152d36dceed646158d8aff990acafbab", | |
| "af34852df5334695b5b767a3884bc91f", | |
| "fdead316ad144f608869b7c34f1d1514" | |
| ] | |
| }, | |
| "id": "_LOdpM-w275E", | |
| "outputId": "eb206bfc-af64-42b3-caaf-39355f928d76" | |
| }, | |
| "source": [ | |
| "# COMMON VOICE VIETNAMESE\n", | |
| "results_common = test_dataset_common.map(map_to_result)\n", | |
| "print(\"Test WER: {:.5f}\".format(wer_metric.compute(predictions=results_common[\"pred_str\"], references=results_common[\"target_text\"])))\n", | |
| "print(\"Test WER: {:.5f}\".format(wer_metric.compute(predictions=results_common[\"pred_str_beam\"], references=results_common[\"target_text\"])))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "1aff7fc4351345fbbdfe37841aa08f11", | |
| "version_minor": 0, | |
| "version_major": 2 | |
| }, | |
| "text/plain": [ | |
| " 0%| | 0/761 [00:00<?, ?ex/s]" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Test WER: 0.18344\n", | |
| "Test WER: 0.11523\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 83, | |
| "referenced_widgets": [ | |
| "bab8f7dfa1cb433eb2590607d00d145a", | |
| "40bf4c2e75c243738089fb6cf7d84ccf", | |
| "59bbfa81e48943988a4415484ef75b90", | |
| "e04588f2fec3424595135296761514fe", | |
| "13d7ea9f8c534e86a926a7f0489d880e", | |
| "b2271d062ece426b84f45c994be562d5", | |
| "60e079bbfb504abb8bd0a91f4a686c3c", | |
| "16d2ea65f81c401f9728f7f0aee33743", | |
| "6917305c3a5b42319348bc3f9b80e6f3", | |
| "00fcb86b1ad345dfa99cfe360f19ae2f", | |
| "85107cd3d5cb4395b91f4058c622fa60" | |
| ] | |
| }, | |
| "id": "SQQeD8bCRX-r", | |
| "outputId": "dd937555-575a-40d3-85a3-c7e7188679a6" | |
| }, | |
| "source": [ | |
| "# VIVOS\n", | |
| "results_vivos = test_dataset_vivos.map(map_to_result)\n", | |
| "print(\"Test WER: {:.5f}\".format(wer_metric.compute(predictions=results_vivos[\"pred_str\"], references=results_vivos[\"target_text\"])))\n", | |
| "print(\"Test WER: {:.5f}\".format(wer_metric.compute(predictions=results_vivos[\"pred_str_beam\"], references=results_vivos[\"target_text\"])))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "bab8f7dfa1cb433eb2590607d00d145a", | |
| "version_minor": 0, | |
| "version_major": 2 | |
| }, | |
| "text/plain": [ | |
| " 0%| | 0/760 [00:00<?, ?ex/s]" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Test WER: 0.10774\n", | |
| "Test WER: 0.06151\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "-V_Fw-wMU6Qp", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 83, | |
| "referenced_widgets": [ | |
| "7dcf5b66b2f848cdb928159949f04456", | |
| "4500810e43c4427e9a75088ada21da60", | |
| "0360ada0de32460aa2553f864ab1cd0c", | |
| "43689d3c564740f3a79840ce18f92191", | |
| "b2cc394b769d4589b4f3b9f7628a7c8a", | |
| "7a68cb2c83e44d6ca7274f279206c031", | |
| "8ce407354781435381275d9e9cddb29d", | |
| "324ed59451164031b302e9cd9c307f4c", | |
| "99a5624850814ed2888a8a72f84a5fb6", | |
| "ae53136477984344bbd5fcb7d95da149", | |
| "8ff64fafd5174346bc60ae7554f592b5" | |
| ] | |
| }, | |
| "outputId": "188f7e90-fda5-4c13-cbe8-eea39e4c7448" | |
| }, | |
| "source": [ | |
| "# T1\n", | |
| "results_t1 = test_dataset_t1.map(map_to_result)\n", | |
| "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results_t1[\"pred_str\"], references=results_t1[\"target_text\"])))\n", | |
| "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results_t1[\"pred_str_beam\"], references=results_t1[\"target_text\"])))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "7dcf5b66b2f848cdb928159949f04456", | |
| "version_minor": 0, | |
| "version_major": 2 | |
| }, | |
| "text/plain": [ | |
| " 0%| | 0/7072 [00:00<?, ?ex/s]" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Test WER: 0.133\n", | |
| "Test WER: 0.091\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 83, | |
| "referenced_widgets": [ | |
| "e85fbd4338a94e86a3d493eaf4ef4534", | |
| "5c844cb17bc64aeb810e530d551c9c3c", | |
| "eaf60db5de2f4e819a5d300f2a0427d0", | |
| "b8fc694cf5e74da9a7a56b3ec5273aee", | |
| "7e7711ca5836422497af65cb8ace9d75", | |
| "a58fc6870d9f4e42a9a522ab59d946f5", | |
| "affc0c5dd7d444c8b15a7a1986894554", | |
| "34b30414c8c34df88bb9bfc30184b872", | |
| "0ec3d5c2b54945b18cfd8924f0b6d6b4", | |
| "b14c32833fca4f948ab3270af2c3248f", | |
| "9c160e343f9245ba917f0e96fa2fb437" | |
| ] | |
| }, | |
| "id": "itBLJVazAEK9", | |
| "outputId": "96679855-bca1-47e6-f1e8-fb0e4580331c" | |
| }, | |
| "source": [ | |
| "# T2\n", | |
| "results_t2 = test_dataset_t2.map(map_to_result)\n", | |
| "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results_t2[\"pred_str\"], references=results_t2[\"target_text\"])))\n", | |
| "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results_t2[\"pred_str_beam\"], references=results_t2[\"target_text\"])))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "e85fbd4338a94e86a3d493eaf4ef4534", | |
| "version_minor": 0, | |
| "version_major": 2 | |
| }, | |
| "text/plain": [ | |
| " 0%| | 0/18788 [00:00<?, ?ex/s]" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Test WER: 0.514\n", | |
| "Test WER: 0.408\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "IQQQhKrTogz3" | |
| }, | |
| "source": [ | |
| "# Split long audio" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "hNZ8y4s3okKr", | |
| "outputId": "da682524-a017-4b08-f7a5-71b26dc0ea82" | |
| }, | |
| "source": [ | |
| "# https://pytorch.org/hub/snakers4_silero-vad_vad/\n", | |
| "import torch\n", | |
| "import onnxruntime\n", | |
| "from pprint import pprint\n", | |
| "from pydub import AudioSegment\n", | |
| "\n", | |
| "_, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad',\n", | |
| " model='silero_vad',\n", | |
| " force_reload=True)\n", | |
| "\n", | |
| "(get_speech_ts,\n", | |
| " get_speech_ts_adaptive,\n", | |
| " _, read_audio,\n", | |
| " _, _, _) = utils\n", | |
| "files_dir = torch.hub.get_dir() + '/snakers4_silero-vad_master/files'\n", | |
| "def init_onnx_model(model_path: str):\n", | |
| " return onnxruntime.InferenceSession(model_path)\n", | |
| "\n", | |
| "def validate_onnx(model, inputs):\n", | |
| " with torch.no_grad():\n", | |
| " ort_inputs = {'input': inputs.cpu().numpy()}\n", | |
| " outs = model.run(None, ort_inputs)\n", | |
| " outs = [torch.Tensor(x) for x in outs]\n", | |
| " return outs[0]\n", | |
| "\n", | |
| "model = init_onnx_model(f'{files_dir}/model.onnx')\n", | |
| "\n", | |
| "def long_speech_file_to_array_fn(path, max_seconds=5):\n", | |
| " input_audio_path = path\n", | |
| " if input_audio_path.endswith('m4a'):\n", | |
| " track = AudioSegment.from_file(input_audio_path,'m4a')\n", | |
| " input_audio_path_extentions = input_audio_path.split('.')[-1]\n", | |
| " input_audio_path = input_audio_path.replace(input_audio_path_extentions, 'wav')\n", | |
| " print(input_audio_path)\n", | |
| " # input_audio_path = '/content/test.wav'\n", | |
| " track.export(input_audio_path, format='wav')\n", | |
| " batch = {\"file\": input_audio_path}\n", | |
| " speech_array, sampling_rate = torchaudio.load(batch[\"file\"])\n", | |
| " if sampling_rate != 16000:\n", | |
| " transform = torchaudio.transforms.Resample(orig_freq=sampling_rate,\n", | |
| " new_freq=16000)\n", | |
| " speech_array = transform(speech_array)\n", | |
| " speech_array = speech_array[0]\n", | |
| " # split long audio by VAD\n", | |
| " if max_seconds*16000 < len(speech_array):\n", | |
| " print(\"split long audio by VAD\", max_seconds*16000, len(speech_array))\n", | |
| " chunks = get_speech_ts(speech_array, model, \n", | |
| " # trig_sum=0.5, \n", | |
| " # neg_trig_sum=0.45, \n", | |
| " num_steps=4,\n", | |
| " # visualize_probs=False, \n", | |
| " run_function=validate_onnx, \n", | |
| " min_speech_samples=10000, \n", | |
| " # min_silence_samples=0,\n", | |
| " # smoothed_prob_func='mean',\n", | |
| " )\n", | |
| " else:\n", | |
| " # print(\"No split long audio by VAD\")\n", | |
| " chunks = [{'end': len(speech_array), 'start': 0}]\n", | |
| " speech_array = speech_array.numpy()\n", | |
| " batches = []\n", | |
| " for chunk in chunks:\n", | |
| " batches.append({\n", | |
| " \"speech\": speech_array[chunk['start']: chunk['end']],\n", | |
| " \"sampling_rate\": 16000\n", | |
| " })\n", | |
| " return batches" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Downloading: \"https://github.com/snakers4/silero-vad/archive/master.zip\" to /root/.cache/torch/hub/master.zip\n" | |
| ], | |
| "name": "stderr" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "XCmXrTNV5Na7" | |
| }, | |
| "source": [ | |
| "# Interaction test" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "1_ECevWx9pXH", | |
| "colab": { | |
| "resources": { | |
| "http://localhost:8080/nbextensions/google.colab/files.js": { | |
| "data": 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| |
| "ok": true, | |
| "headers": [ | |
| [ | |
| "content-type", | |
| "application/javascript" | |
| ] | |
| ], | |
| "status": 200, | |
| "status_text": "" | |
| } | |
| }, | |
| "base_uri": "https://localhost:8080/", | |
| "height": 215 | |
| }, | |
| "cellView": "form", | |
| "outputId": "4e81b02f-b5f7-425a-ca78-7376f94bcc77" | |
| }, | |
| "source": [ | |
| "#@markdown Either record audio from microphone or upload audio from file (.mp3 or .wav) { run: \"auto\" }\n", | |
| "record_or_upload = \"Upload (.mp3 or .wav)\" #@param [\"Record\", \"Upload (.mp3 or .wav)\"]\n", | |
| "record_seconds = 5#@param {type:\"number\", min:1, max:10, step:1}\n", | |
| "sample_rate = 16000\n", | |
| "\n", | |
| "import ipywidgets as widgets\n", | |
| "from scipy.io import wavfile\n", | |
| "from IPython.display import Audio, display, clear_output\n", | |
| "import io\n", | |
| "import base64\n", | |
| "import tempfile\n", | |
| "from typing import Optional\n", | |
| "from pydub import AudioSegment\n", | |
| "from google.colab import files\n", | |
| "from google.colab import output\n", | |
| "from IPython import display as _display\n", | |
| "import torchaudio\n", | |
| "import numpy as np\n", | |
| "import time\n", | |
| "\n", | |
| "def read_audio(path: str,\n", | |
| " target_sr: int = 16000):\n", | |
| "\n", | |
| " wav, sr = torchaudio.load(path)\n", | |
| "\n", | |
| " if wav.size(0) > 1:\n", | |
| " wav = wav.mean(dim=0, keepdim=True)\n", | |
| "\n", | |
| " if sr != target_sr:\n", | |
| " transform = torchaudio.transforms.Resample(orig_freq=sr,\n", | |
| " new_freq=target_sr)\n", | |
| " wav = transform(wav)\n", | |
| " sr = target_sr\n", | |
| "\n", | |
| " assert sr == target_sr\n", | |
| " return wav.squeeze(0)\n", | |
| "\n", | |
| "def record_audio(seconds: int = 3,\n", | |
| " normalize_db: float = 0.1):\n", | |
| " # Use Javascript to record audio.\n", | |
| " record_js_code = \"\"\"\n", | |
| " const sleep = time => new Promise(resolve => setTimeout(resolve, time))\n", | |
| " const b2text = blob => new Promise(resolve => {\n", | |
| " const reader = new FileReader()\n", | |
| " reader.onloadend = e => resolve(e.srcElement.result)\n", | |
| " reader.readAsDataURL(blob)\n", | |
| " })\n", | |
| " var record = time => new Promise(async resolve => {\n", | |
| " stream = await navigator.mediaDevices.getUserMedia({ audio: true })\n", | |
| " recorder = new MediaRecorder(stream)\n", | |
| " chunks = []\n", | |
| " recorder.ondataavailable = e => chunks.push(e.data)\n", | |
| " recorder.start()\n", | |
| " await sleep(time)\n", | |
| " recorder.onstop = async ()=>{\n", | |
| " blob = new Blob(chunks)\n", | |
| " text = await b2text(blob)\n", | |
| " resolve(text)\n", | |
| " }\n", | |
| " recorder.stop()\n", | |
| " })\n", | |
| " \"\"\"\n", | |
| " print('Starting recording for {} seconds...'.format(seconds))\n", | |
| " _display.display(_display.Javascript(record_js_code))\n", | |
| " audio_string = output.eval_js('record(%d)' % (seconds * 1000.0))\n", | |
| " print('Finished recording!')\n", | |
| " audio_bytes = base64.b64decode(audio_string.split(',')[1])\n", | |
| " return audio_bytes_to_np(audio_bytes,\n", | |
| " normalize_db=normalize_db)\n", | |
| "\n", | |
| "\n", | |
| "def audio_bytes_to_np(wav_data: bytes,\n", | |
| " normalize_db: float = 0.1):\n", | |
| " # Parse and normalize the audio.\n", | |
| " audio = AudioSegment.from_file(io.BytesIO(wav_data))\n", | |
| " audio.remove_dc_offset()\n", | |
| " if normalize_db is not None:\n", | |
| " audio.normalize(headroom=normalize_db)\n", | |
| " # Save to tempfile and load with librosa.\n", | |
| " with tempfile.NamedTemporaryFile(suffix='.wav') as temp_wav_file:\n", | |
| " fname = temp_wav_file.name\n", | |
| " audio.export(fname, format='wav')\n", | |
| " wav = read_audio(fname)\n", | |
| " return wav\n", | |
| "\n", | |
| "\n", | |
| "def upload_audio(normalize_db: Optional[float] = None):\n", | |
| " audio_files = files.upload()\n", | |
| " fnames = list(audio_files.keys())\n", | |
| " if len(fnames) == 0:\n", | |
| " return None\n", | |
| " return read_audio(fnames[0])\n", | |
| "\n", | |
| "def wav_to_text():\n", | |
| " input_batch = speech_file_to_array_fn('test.wav')\n", | |
| " output = map_to_result(input_batch)\n", | |
| " return output[\"pred_str_beam\"]\n", | |
| "\n", | |
| "def _recognize(audio):\n", | |
| " display(Audio(audio, rate=sample_rate, autoplay=True))\n", | |
| " # if use_VAD == \"Yes\":\n", | |
| " # audio = _apply_vad(audio)\n", | |
| " wavfile.write('test.wav', sample_rate, (32767*audio).numpy().astype(np.int16))\n", | |
| " start_time = time.time()\n", | |
| " transcription = wav_to_text()\n", | |
| " print('\\n\\nTRANSCRIPTION in {:.3f}s:\\n'.format(time.time() - start_time))\n", | |
| " print(transcription)\n", | |
| "\n", | |
| "def _record_audio(b):\n", | |
| " clear_output()\n", | |
| " audio = record_audio(record_seconds)\n", | |
| " wavfile.write('recorded.wav', sample_rate, (32767*audio).numpy().astype(np.int16))\n", | |
| " _recognize(audio)\n", | |
| "\n", | |
| "def _upload_audio(b):\n", | |
| " clear_output()\n", | |
| " audio = upload_audio()\n", | |
| " _recognize(audio)\n", | |
| " return audio\n", | |
| "\n", | |
| "\n", | |
| "if record_or_upload == \"Record\":\n", | |
| " button = widgets.Button(description=\"Record Speech\")\n", | |
| " button.on_click(_record_audio)\n", | |
| " display(button)\n", | |
| "else:\n", | |
| " audio = _upload_audio(\"\")" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "\n", | |
| " <input type=\"file\" id=\"files-9ef56e21-0140-4125-8b53-c30b61b47ea7\" name=\"files[]\" multiple disabled\n", | |
| " style=\"border:none\" />\n", | |
| " <output id=\"result-9ef56e21-0140-4125-8b53-c30b61b47ea7\">\n", | |
| " Upload widget is only available when the cell has been executed in the\n", | |
| " current browser session. Please rerun this cell to enable.\n", | |
| " </output>\n", | |
| " <script src=\"/nbextensions/google.colab/files.js\"></script> " | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Saving VIVOSDEV02_R106.wav to VIVOSDEV02_R106.wav\n" | |
| ], | |
| "name": "stdout" | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "\n", | |
| " <audio controls=\"controls\" autoplay=\"autoplay\">\n", | |
| " <source 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\" type=\"audio/wav\" />\n", | |
| " Your browser does not support the audio element.\n", | |
| " </audio>\n", | |
| " " | |
| ], | |
| "text/plain": [ | |
| "<IPython.lib.display.Audio object>" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "\n", | |
| "\n", | |
| "TRANSCRIPTION in 0.034s:\n", | |
| "\n", | |
| "trở nên thụ động\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "DApYGigghLdW" | |
| }, | |
| "source": [ | |
| "# Web interface interaction test" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 640 | |
| }, | |
| "id": "mrh38iWVhK7U", | |
| "outputId": "ce594d7d-5959-42e3-c4c1-7b6feb655d15" | |
| }, | |
| "source": [ | |
| "import gradio as gr\n", | |
| "import time\n", | |
| "def voicerec(aud):\n", | |
| " # input_batch = speech_file_to_array_fn(aud.name, max_seconds=10)\n", | |
| " input_batches = long_speech_file_to_array_fn(aud.name)\n", | |
| " outputs = []\n", | |
| " for input_batch in input_batches:\n", | |
| " start_time = time.time()\n", | |
| " output_result = map_to_result(input_batch)\n", | |
| " outputs.append({\n", | |
| " \"output\": output_result['pred_str_beam'],\n", | |
| " # \"ctc_output\": output_result['pred_str'],\n", | |
| " \"time_infer\": \"{:.5f}s\".format(time.time() - start_time)\n", | |
| " })\n", | |
| " return {\n", | |
| " \"output\": \" \".join([item['output'] for item in outputs]), \n", | |
| " \"shards\": outputs\n", | |
| " }\n", | |
| "input = gr.inputs.Audio(label=\"Input Audio\", type=\"file\") \n", | |
| "output = gr.outputs.JSON(label=\"ASR result\")\n", | |
| "\n", | |
| "\n", | |
| "title = \"Automatic Speech Recognition with Wav2vec\"\n", | |
| "description = \"Upload audio file (<10s) then submit. \"\n", | |
| "examples = [[]]\n", | |
| "\n", | |
| "gr.Interface(voicerec, input, output, title=title, description=description, examples=examples).launch()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Colab notebook detected. To show errors in colab notebook, set `debug=True` in `launch()`\n", | |
| "This share link will expire in 24 hours. If you need a permanent link, visit: https://gradio.app/introducing-hosted (NEW!)\n", | |
| "Running on External URL: https://27576.gradio.app\n", | |
| "Interface loading below...\n" | |
| ], | |
| "name": "stdout" | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "\n", | |
| " <iframe\n", | |
| " width=\"900\"\n", | |
| " height=\"500\"\n", | |
| " src=\"https://27576.gradio.app\"\n", | |
| " frameborder=\"0\"\n", | |
| " allowfullscreen\n", | |
| " ></iframe>\n", | |
| " " | |
| ], | |
| "text/plain": [ | |
| "<IPython.lib.display.IFrame at 0x7fc571966550>" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "(<Flask 'gradio.networking'>,\n", | |
| " 'http://127.0.0.1:7860/',\n", | |
| " 'https://27576.gradio.app')" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 11 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "DImR2W3826tU" | |
| }, | |
| "source": [ | |
| "# Show eval samples" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "CrqE-RYr28eZ" | |
| }, | |
| "source": [ | |
| "from datasets import ClassLabel\n", | |
| "import random\n", | |
| "import pandas as pd\n", | |
| "from IPython.display import display, HTML\n", | |
| "\n", | |
| "def show_random_elements(dataset, columns, num_examples=10):\n", | |
| " assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n", | |
| " picks = []\n", | |
| " for _ in range(num_examples):\n", | |
| " pick = random.randint(0, len(dataset)-1)\n", | |
| " while pick in picks:\n", | |
| " pick = random.randint(0, len(dataset)-1)\n", | |
| " picks.append(pick)\n", | |
| " \n", | |
| " df = pd.DataFrame(dataset[picks], columns=columns)\n", | |
| " display(HTML(df.to_html()))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 979 | |
| }, | |
| "id": "Nic-d32I7JLw", | |
| "outputId": "f8adbf5c-26f3-437b-ac09-350b6435380a" | |
| }, | |
| "source": [ | |
| "show_random_elements(results_common, columns=['target_text', 'pred_str_beam', 'pred_str'], num_examples=30)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>target_text</th>\n", | |
| " <th>pred_str_beam</th>\n", | |
| " <th>pred_str</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>vậy mà quân vẫn lạnh lùng vô cảm</td>\n", | |
| " <td>vậy mà quân vẫn lạnh lùng tôn cảm</td>\n", | |
| " <td>vậy mà quân vẫn lạnh lùng tôn cảm</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>trái cây thơm trên miền đất khô cằn</td>\n", | |
| " <td>trái cây thơm trên miền đất khô cằn</td>\n", | |
| " <td>trái cây thơm trên miền đất khu cản</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>em run giọng nói</td>\n", | |
| " <td>em hương giọng nói</td>\n", | |
| " <td>em hương gọng nó</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>khi cô đơn cạn tình ai cũng thế</td>\n", | |
| " <td>khi cô đơn cạnh trình ai cũng thấy nước</td>\n", | |
| " <td>khi cô đơn cạnh trình ai cũng thấy nớ ất</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>tôi có cái ý như thế này</td>\n", | |
| " <td>tôi có cái ý như thế này</td>\n", | |
| " <td>tôi có cái ý như thế này</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>cô thu ngân lo lắng gọi</td>\n", | |
| " <td>cô thương ngăn lo lắng gọi</td>\n", | |
| " <td>cô thương ngăn lo lắng gọi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>họp lớp sau nhiều năm mỗi người một nơi</td>\n", | |
| " <td>họp lớp sau nhiều năm mỗi người một nơi</td>\n", | |
| " <td>họp lớp sau nhiều năm mỗi người một nơi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>em còn hẹn nữa không</td>\n", | |
| " <td>em còn hẹn nữa không</td>\n", | |
| " <td>em còn hẹ nữa không</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>anh chàng lái xe do vậy không thể nói tiếp điều đang muốn nói</td>\n", | |
| " <td>anh chàng lái xe do vậy không thể nói tiết điều đang muốn nói</td>\n", | |
| " <td>anh chàng lái xe do vậy không thể nói tiếc điều đang muốn nói</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>em cũng không có biết đâu</td>\n", | |
| " <td>em cũng không có biết đâu</td>\n", | |
| " <td>em cũng không có biết đâu</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>hắn đang đi lên đây</td>\n", | |
| " <td>hắn đang đi lên đây</td>\n", | |
| " <td>thắn đang đi lên đây</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>nó còn bảo là hôm nay nó muốn con đưa đi chơi cùng</td>\n", | |
| " <td>nó còn bảo là hôm nay nó muốn con đưa đi chơi cùng</td>\n", | |
| " <td>nó còn bảo là hôm nay nó muốn con đưa đi chơi cùng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>nhà mới của em ở trong xóm</td>\n", | |
| " <td>nhà mới của em ở trung sơn</td>\n", | |
| " <td>nhà mới của em ở trùng sớm</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>nó cứ nhìn chằm chằm vào đó</td>\n", | |
| " <td>nó cứ nhìn chằm chằm vào đó</td>\n", | |
| " <td>nó cứ nhìn chằm crằm vào đó</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>anh chị chào mào</td>\n", | |
| " <td>anh chị chào nào</td>\n", | |
| " <td>anh chị chào nào</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>trời tháng mườimây vờn bay bảng lãng</td>\n", | |
| " <td>trời tháng mười mây vờn bay bảng lạng</td>\n", | |
| " <td>trời tháng mười mâ vờn bay bảng lạng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>kẻ bất tài</td>\n", | |
| " <td>kẻ bất tài</td>\n", | |
| " <td>kẻ bất tài</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>nhưng đến thật bất ngờ</td>\n", | |
| " <td>nhưng đến thật bất ngờ</td>\n", | |
| " <td>nhưng đến thịt bất ngờ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>bàn chân nào ở lại</td>\n", | |
| " <td>bàn chân nào ở lại</td>\n", | |
| " <td>bàn chân nào ở lại</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>đừng có chết đấy</td>\n", | |
| " <td>đừng có chết đấy</td>\n", | |
| " <td>đừng có chết đấy</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>tiếng nói lại vang lên rất khẽ chỉ đủ cho mình nghe</td>\n", | |
| " <td>tiếng nói lại mang lên rất khẽ chỉ đụng cho mình he</td>\n", | |
| " <td>tiếng nói lại bang lên rất gẽ chỉ đụng cho mình e</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>sao mày nói dù chuyện gì cũng xảy ra</td>\n", | |
| " <td>sao mày nói dù chuyện gì cũng xảy ra</td>\n", | |
| " <td>sao mày nói dù chuyện gì cũng xảy ra</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>tiếng chuông đồng hồ quả lắc vang lên</td>\n", | |
| " <td>tiếng chuông đồng hồ quả lắc vang lên</td>\n", | |
| " <td>tiếng chuông đồng hồ quả lắp vang lên</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>những chiếc lá trút xuống đời thật tội</td>\n", | |
| " <td>những chiếc lá trút xuống đời thích tội</td>\n", | |
| " <td>những chiếc lá trút xuống đời thích tội</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>các cô cậu đều là người ở dưới xuôi lên</td>\n", | |
| " <td>các cô cậu đều là người ở dưới xuôi lên</td>\n", | |
| " <td>các cô cậu đều là người ở dưới suôi nêm</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>tại quảng trường ba đình</td>\n", | |
| " <td>tại quảng trường ba đình</td>\n", | |
| " <td>tại quảng trường ba tỉnh</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>ai vậy</td>\n", | |
| " <td>ai vậy</td>\n", | |
| " <td>ai vậy</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>dạ bẩm thầy giờ đã muộn rồi à</td>\n", | |
| " <td>giả bấm thầy giờ đã muộn rồi hàng</td>\n", | |
| " <td>giả bẫm thầy giờ đã muộn rồi hàng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>hà ni ngỡ rằng anh ta đóng kịch</td>\n", | |
| " <td>hà ny ngờ rằng anh ta đóng kịch</td>\n", | |
| " <td>hà ny ngớ rằng anh ta đóng kịch</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>đến bố mẹ còn chẳng nhận ra cháu ạ</td>\n", | |
| " <td>đến bố mẹ còn chẳng nhận ra cháu</td>\n", | |
| " <td>đến bố mẹ còn chẳng nhận ra cháu ả</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| }, | |
| "id": "aLZ5StKj29WC", | |
| "outputId": "f2007d41-707d-4f08-a5df-582e45b9017f" | |
| }, | |
| "source": [ | |
| "show_random_elements(results_t2, columns=['id', 'target_text', 'pred_str_beam', 'pred_str'], num_examples=30)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>id</th>\n", | |
| " <th>target_text</th>\n", | |
| " <th>pred_str_beam</th>\n", | |
| " <th>pred_str</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>0000013121</td>\n", | |
| " <td>to lên</td>\n", | |
| " <td>to lên</td>\n", | |
| " <td>bo lên</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>0000005934</td>\n", | |
| " <td>tăng âm lượng</td>\n", | |
| " <td>tăng âm lượng</td>\n", | |
| " <td>tăng âm lượng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>0000013396</td>\n", | |
| " <td>tiếng tắt</td>\n", | |
| " <td>điện cực</td>\n", | |
| " <td>điện cức</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>0000013523</td>\n", | |
| " <td>kênh giảm</td>\n", | |
| " <td>canh giờ</td>\n", | |
| " <td>tanh gờ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>0000003248</td>\n", | |
| " <td>ti vi âm lượng tăng</td>\n", | |
| " <td>bị âm lượng tăng</td>\n", | |
| " <td>ti bị âm lợn tăng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>0000002915</td>\n", | |
| " <td>quạt số hai</td>\n", | |
| " <td>và số hai</td>\n", | |
| " <td>vạ số hai</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>0000010018</td>\n", | |
| " <td>tắt đèn</td>\n", | |
| " <td>rất đàn</td>\n", | |
| " <td>rất đèn</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>0000008358</td>\n", | |
| " <td>giảm</td>\n", | |
| " <td>gam</td>\n", | |
| " <td>gam</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>0000004603</td>\n", | |
| " <td>ti vi tiếng tắt</td>\n", | |
| " <td>ti vi tiếng tắt</td>\n", | |
| " <td>ti vi tiếng tắt</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>0000010394</td>\n", | |
| " <td>kênh giảm</td>\n", | |
| " <td>cảnh sát</td>\n", | |
| " <td>canh xá</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>0000015809</td>\n", | |
| " <td>giảm đi</td>\n", | |
| " <td>giảm đi</td>\n", | |
| " <td>giảm đi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>0000009877</td>\n", | |
| " <td>bật điều hòa</td>\n", | |
| " <td>bật điều hòa</td>\n", | |
| " <td>bật điều hòa</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>0000006682</td>\n", | |
| " <td>âm lượng ti vi giảm</td>\n", | |
| " <td>âm lượng ti vi giảm</td>\n", | |
| " <td>âm lượng ti vi gản</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>0000014050</td>\n", | |
| " <td>điều hòa tắt</td>\n", | |
| " <td>chiều hòa tấp</td>\n", | |
| " <td>chều hòa tấp</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>0000018323</td>\n", | |
| " <td>nên em hay trách chuyện của em nói đang để trong lòng bạn nói với chị họ của em á là phước yêu cầu những những cái đề nghị để cho bạn em sửa chữa đó thì bạn em làm không được</td>\n", | |
| " <td>em hay trách chuyện của em nói bạn để trong lòng bạn nói với chị họ của em á là phước yêu cầu những những cái đề nghị để cho bạn em sửa chữa đó thì bạn em làm không được</td>\n", | |
| " <td>em hay chách chuyện của em nói bạng đợ trong lòng bạn nói với chị họ của em á là phước yêu cầu những những cái đề nghị để cho bạn em sửa chữa đó thì bạn e làm không được</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>0000004087</td>\n", | |
| " <td>bật quạt</td>\n", | |
| " <td>bách quan</td>\n", | |
| " <td>bệch quan</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>0000006444</td>\n", | |
| " <td>tắt đèn đi</td>\n", | |
| " <td>bắt bẻ đi</td>\n", | |
| " <td>bát bè đi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>0000017016</td>\n", | |
| " <td>đèn bật</td>\n", | |
| " <td>đèn bật</td>\n", | |
| " <td>đèn mật</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>0000015131</td>\n", | |
| " <td>nhỏ quạt đi</td>\n", | |
| " <td>quá đi</td>\n", | |
| " <td>nà qá đi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>0000004101</td>\n", | |
| " <td>giảm quạt đi</td>\n", | |
| " <td>dạng quạt đi</td>\n", | |
| " <td>dạng quạt đi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>0000004046</td>\n", | |
| " <td>nhỏ đi</td>\n", | |
| " <td>nhỏ đi</td>\n", | |
| " <td>nhỏ đi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>0000009302</td>\n", | |
| " <td>bật quạt</td>\n", | |
| " <td>bật quạt</td>\n", | |
| " <td>bật quảc</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>0000002419</td>\n", | |
| " <td>tắt đèn</td>\n", | |
| " <td>áp đen</td>\n", | |
| " <td>áp đèn</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>0000017902</td>\n", | |
| " <td>nhỏ</td>\n", | |
| " <td></td>\n", | |
| " <td>i</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>0000006992</td>\n", | |
| " <td>bật âm ti vi</td>\n", | |
| " <td>bật âm ti vi</td>\n", | |
| " <td>bặt ân thi vi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>0000017501</td>\n", | |
| " <td>quạt tăng lên</td>\n", | |
| " <td>và tăng ni</td>\n", | |
| " <td>vàt thăng hy</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>0000013968</td>\n", | |
| " <td>ti vi kênh giảm</td>\n", | |
| " <td>ti vi kênh giảm</td>\n", | |
| " <td>tivi cênh gậm</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>0000009720</td>\n", | |
| " <td>tắt đèn</td>\n", | |
| " <td>tác càng</td>\n", | |
| " <td>tác càn</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>0000001798</td>\n", | |
| " <td>nhỏ</td>\n", | |
| " <td>nhờ</td>\n", | |
| " <td>nhà</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>0000008827</td>\n", | |
| " <td>đèn tắt đi</td>\n", | |
| " <td>đèn tắt đi</td>\n", | |
| " <td>đen tắt đi</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
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| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| }, | |
| "id": "lvVfUgXh3D4a", | |
| "outputId": "a644777e-e877-4d3c-dcbe-d0f31abfb73d" | |
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| "show_random_elements(results_t1, columns=['id', 'target_text', 'pred_str_beam', 'pred_str'], num_examples=30)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
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| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>id</th>\n", | |
| " <th>target_text</th>\n", | |
| " <th>pred_str_beam</th>\n", | |
| " <th>pred_str</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>program-0014-00222</td>\n", | |
| " <td>à vâng thưa nhà biên kịch trịnh thanh nhã ờ</td>\n", | |
| " <td>ờ vâng thôi nhà biên kịch trịnh thanh nhã à</td>\n", | |
| " <td>ờ vâng thơ nhà biên kịch trịnh thanh nhã ờ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>program-0019-00392</td>\n", | |
| " <td>không sao đâu ạ mẹ cứ ngủ thế đi không sao</td>\n", | |
| " <td>không sao đâu ạ mẹ cứ ngủ thế đi không sao</td>\n", | |
| " <td>không sao đâu ạ mẹ cứ ngủ thế đi công sao</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>program-0079-00113</td>\n", | |
| " <td>nó không có cái gì thú vị hết tuấn kiệt thì em nghĩ là ừm em đánh giá gì về bồ độ em đang mặc</td>\n", | |
| " <td>nó không có cái gì thú vị hết ấn kiệt thì em nghĩ là em đánh giá gì về bộ đồ em đang mặc</td>\n", | |
| " <td>nó không có cái gì thú vị hết ấn kiệt thì em nghĩ là em đánh giá gì về bồ đồm em đăng mặt</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>program-0021-00224</td>\n", | |
| " <td>làm trò để trêu các bạn cười rồi bắt lên hít đất</td>\n", | |
| " <td>làm trò để trêu các bạn cười rồi vắt lên hít đất</td>\n", | |
| " <td>làm trò để trêo các bạn cười rồi vắt lên thích đất</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>spk20h-000006-utt000000074</td>\n", | |
| " <td>con cũng chưa tính ạ</td>\n", | |
| " <td>quang cũng chưa tính ạ</td>\n", | |
| " <td>qăng cũng chưa tính ạ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>program-0015-00318</td>\n", | |
| " <td>thưa quý vị và các bạn tôi đang cầm trên tay thanh sắt thông thường và vật liệu</td>\n", | |
| " <td>thưa quý vị và các bạn tôi đang cầm trên tay thanh sắt thông thường và vật</td>\n", | |
| " <td>thưa quý vị và các bạn tôi đang cầm trên tay thanh sắt không thường và vật</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>program-0074-00195</td>\n", | |
| " <td>à cái người bán hàng họ phát hiện ra mình là người chụp chợ họ xin chụp chung với mình</td>\n", | |
| " <td>cái người bán hàng họ phát hiện ra mình mọi người chụp chợ hình chụp chung với mình</td>\n", | |
| " <td>cái người bán hàng họ phát hiện ra mình mọi người chục chợ sình chụp chung với mình</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>program-0115-00262</td>\n", | |
| " <td>nhận ra rằng thất bại không phải là bức tường cao khó vượt qua đến thế</td>\n", | |
| " <td>nhận ra rằng thất bại không phải là bức tượng cao khó vượt qua đến thế</td>\n", | |
| " <td>nhận ra rằng thất bại không phải là bức tượng cao khó vượt qua đếm thê</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>spk20h-000044-utt000000042</td>\n", | |
| " <td>những nơi đã khống chế được căn bệnh</td>\n", | |
| " <td>những nơi đã khống chế được căn bệnh</td>\n", | |
| " <td>những nơi đã không chế được căn bệnh</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>program-0033-00463</td>\n", | |
| " <td>mọi người sẽ bị nhàm chán là trong cái việc là em á</td>\n", | |
| " <td>mọi người sẽ bị nhàm chán là trong cái việc mà em</td>\n", | |
| " <td>mọi người sẽ bị nhàm trán là trong cái việc là em</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>program-0021-00140</td>\n", | |
| " <td>không hề có kiến thức về bóng đá mà lại lên bình luận bàn luận về bóng đá thì đó là một điều</td>\n", | |
| " <td>không hề có kiến thức về bóng đá mà lại lên bình luận bàn luận về bóng đá thì đó là điều</td>\n", | |
| " <td>không hề có kiến thức về bóng đá mà lại lên bình luận vàng luận về bóng đá thì đó là điều</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>program-0105-00302</td>\n", | |
| " <td>lớp chỉ là cái cớ để nó khoe mẽ thôi</td>\n", | |
| " <td>lớp chỉ là cái cớ để nó khoe mẽ thôi</td>\n", | |
| " <td>lớp chỉ là cái cưới để nó khoe mẻ thôi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>program-0147-00533</td>\n", | |
| " <td>và trường hợp mà lừa tiền không biết là bao nhiêu lần để mà kể lại nó rất là nhiều lần rồi</td>\n", | |
| " <td>và trường hợp mà lừa tiền không biết là bao nhiêu lần để mà kể lại nó rất là nhiều lần rồi</td>\n", | |
| " <td>và trường hợp mà lừa tiền không biết là bao nhiêu lần để mà kể lại nó rất là nhiều lần rồi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>spk20h-000003-utt000000071</td>\n", | |
| " <td>bé hà vội vàng giới thiệu</td>\n", | |
| " <td>đã hà vội vàng giới thiệu</td>\n", | |
| " <td>đã hà vội vàn giới thiệu</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>program-0031-00524</td>\n", | |
| " <td>và anh em chúng tôi đã có những hiến kế như thế thì hy vọng là có thể</td>\n", | |
| " <td>và nghe chúng tôi đã có những cái như thế như thế hy vọng là có thể</td>\n", | |
| " <td>vànhnghe chúng tôi đã có những c nư kế như thế hy vọng là có thể</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>spk20h-000091-utt000000122</td>\n", | |
| " <td>tôi còn cùng gia đình gấp rút làm nhanh căn nhà này</td>\n", | |
| " <td>tôi còn cùng gia đình gấp rút làm nhanh căn nhà này</td>\n", | |
| " <td>tôi còn cùng gia đình gớp rút làm nhanh căn nhà này</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>program-0152-00611</td>\n", | |
| " <td>ờ và anh xã thì thiên về lý trí còn ánh tuyết thì sống thiên về tình cảm</td>\n", | |
| " <td>và anh xã thì thiên về lý trí còn ánh tuyết thì sống thiên về tình cảm</td>\n", | |
| " <td>ờvà anh xã thì thiên về lý trí còn ánh tuyết thì sống thiên về tình cảm</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>program-0062-00421</td>\n", | |
| " <td>có nghĩa là em chú ý rất kỹ những điều mà ban giám khảo nói như là hôm qua ngân có nghe một bạn chia sẻ</td>\n", | |
| " <td>có nghĩa là em chủ yếu rất kỹ những điều mà ban giám khảo nói như là hôm qua ngângứgnghemột mẹ chia sẻ</td>\n", | |
| " <td>có nghĩa là em chủ yếu rất kỹ những điều mà ban giám khảo nói như là hôm qua ngân ngứ nghe một bẹ chia sẻ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>program-0021-00004</td>\n", | |
| " <td>lá ngoài đường rụng nhiều hôm nay tôi đi học</td>\n", | |
| " <td>lá ngoài đường rụ gì hôm nay tôi đi</td>\n", | |
| " <td>lá ngoài đường rụ nìu hôm nay tai đi h</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>program-0134-00250</td>\n", | |
| " <td>đúng không đấy là cái hậu quả thứ nhất tức là trở thành đói nghèo từ đói nghèo lại tiếp tục đói nghèo</td>\n", | |
| " <td>đúng không đấy là cái hộ bản nhất tức là trở thành đó nhèo từ đó nhau lại tiếp tục đón nè</td>\n", | |
| " <td>đúng không đấy là cái hộ bản nhất tức là trở thành đó nhèo từ đó nhau lại tiếp tục đón nèo</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>spk20h-000066-utt000000162</td>\n", | |
| " <td>và dậy cho bọn người xấu những bài học nhớ đời</td>\n", | |
| " <td>và dạy cho bọn người xấu những bài học nhớ đời</td>\n", | |
| " <td>và dạnh cho mọn người xấu những bài học nhớ đời</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>program-0014-00066</td>\n", | |
| " <td>muốn đạt được điều đó có lẽ mỗi người cán bộ đều phải nhận thức được vai trò trách nhiệm của mình trong việc phục vụ nhân dân</td>\n", | |
| " <td>muốn đạt được điều đó có lẽ mỗi người cán bộ đều phải nhận thức được vai trò trách nhiệm của mình trong việc phục vụ nhân dân</td>\n", | |
| " <td>muốn đạt được điều đó có lẽ mỗi người cán bộ đều phải nhận thức được vai trò trách nhiệm của mình trong việc phục vụ nhân dân</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>spk20h-000031-utt000000133</td>\n", | |
| " <td>bố</td>\n", | |
| " <td>đúng</td>\n", | |
| " <td>đú</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>program-0022-00668</td>\n", | |
| " <td>con chưa nhớ rõ công thức thì mẹ con sẽ hỗ trợ</td>\n", | |
| " <td>con chưa nhớ võ công sức thì mẹ con sẽ hỗ trợ</td>\n", | |
| " <td>con chưa nhớ võ công sức thì mẹ con sẽ hỗ trợ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>spk20h-000077-utt000000089</td>\n", | |
| " <td>bây giờ tôi đã là y đông</td>\n", | |
| " <td>bây giờ tôi đã là đông</td>\n", | |
| " <td>bây giờ tôi đã là i đâng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>program-0130-00317</td>\n", | |
| " <td>êm ái và nhân văn dạ là khi cháu đang nói chuyện với chú thì cháu đang thực sự cảm nhận là chú vẫn mong muốn mình có được một cơ hội</td>\n", | |
| " <td>em bảo nhân vẫn nhà khi cháu đang nói chuyện với chú thì cháu đang thực sự cảm nhận là chú vẫn mong muốn mình có được một cơ hội</td>\n", | |
| " <td>ìm i bào nhân vẫn ạ nhà khi cháu đang nói chuyện với chú thì cháu đang thực sự cảm nhận là chú vẫn mong muốn mình có được một cơ hội</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>program-0108-00066</td>\n", | |
| " <td>dù gì ông cũng là một đại gia</td>\n", | |
| " <td>dù gì ông cũng là một đại gia</td>\n", | |
| " <td>dù gì ông cũng là một đại gia</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>program-0111-00553</td>\n", | |
| " <td>khán giả theo dõi chương trình và tham gia bình chọn nhân vật được yêu thích nhất trong tuần sẽ có</td>\n", | |
| " <td>khán giả theo dõi chương trình và tham gia bình chọn nhân vật được yêu thích nhất trong tuần sẽ có</td>\n", | |
| " <td>khán giả theo dõi chương trình và tham gia bình chọn nhân vật được yêu thích nhất trong tuần sẽ có</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>program-0033-00677</td>\n", | |
| " <td>bao giờ cưới bao giờ lấy chồng tao từng ngày tuổi đầu rồi còn chưa có cháu bế rồi</td>\n", | |
| " <td>ba là cưới bao giờ lấy chồng tao từng này tuổi đầu rồi còn chưa có cháu bế rồi</td>\n", | |
| " <td>ba là cưới bao giờ lấy chồng tao từng này tuổi đầu rồi còn chưa có cháu bế rồi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>program-0107-00329</td>\n", | |
| " <td>sẵn tiện á ra mắt tí với anh luôn rồi bà con hàng xóm nữa</td>\n", | |
| " <td>sẵn tiện á ra mắt tí với anh luôn rồi bà con hàng xóm nữa</td>\n", | |
| " <td>sảng tiền á ca mắt tí với anh luôn rồi bà câu hàng xớm nữa</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
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| ], | |
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| "outputs": [ | |
| { | |
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| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>id</th>\n", | |
| " <th>target_text</th>\n", | |
| " <th>pred_str_beam</th>\n", | |
| " <th>pred_str</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>VIVOSDEV02_T004</td>\n", | |
| " <td>hôm nay em có tới năm khách</td>\n", | |
| " <td>hôm nay em có tới năm khác</td>\n", | |
| " <td>hôm nay em có tới năm khác</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>VIVOSDEV13_255</td>\n", | |
| " <td>có lẽ đây là lời quảng cáo không công hay nhất cho du lịch lào</td>\n", | |
| " <td>có lẽ đây là lời quảng cáo không công hay nhất cho du lịch nào</td>\n", | |
| " <td>có lẽ đây là lời quảng cáo không công hay nhất cho du lịch nào</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>VIVOSDEV05_226</td>\n", | |
| " <td>một cú ngoặt không chính xác</td>\n", | |
| " <td>một cú ngoặt không chính xác</td>\n", | |
| " <td>một cú ngoặc không chính xác</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>VIVOSDEV18_250</td>\n", | |
| " <td>lần đầu tiên một nhân viên người việt thách thức việc tác nghiệp của tôi</td>\n", | |
| " <td>lần đầu tiên một nhân viên người việt thách thức việc tác nghiệp của tôi</td>\n", | |
| " <td>lần đầu tiên một nhân viên người việt thách thức việc tác nghiệp của tôi</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>VIVOSDEV11_273</td>\n", | |
| " <td>trọng tài phạt thẻ đỏ</td>\n", | |
| " <td>trọng tài phạt thẻ đỏ</td>\n", | |
| " <td>trọng tài phạt thả đỏ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>VIVOSDEV06_240</td>\n", | |
| " <td>tám mươi sáu tám mươi bảy</td>\n", | |
| " <td>tám mươi sáu tám mươi bảy</td>\n", | |
| " <td>tám mươi sáu tám mươi bảy</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>VIVOSDEV01_R188</td>\n", | |
| " <td>việc quy tội để bùng nổ loại sách này là do</td>\n", | |
| " <td>việc quy tội để bùng nổ loại sách này là do</td>\n", | |
| " <td>việc quy tội để bùng nổ loại sách này là do</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>VIVOSDEV12_275</td>\n", | |
| " <td>tôi không thấy gì là đúng khi tăng giá xe vào các dịp tết</td>\n", | |
| " <td>tôi không thấy gì là đúng khi tăng giá xe vào các dịp tết</td>\n", | |
| " <td>tôi không thấy gì là đúng khi tăng giá xe vào các dịp tết</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>VIVOSDEV01_T043</td>\n", | |
| " <td>nó trốn mất tiêu rồi còn đâu</td>\n", | |
| " <td>nói chốn mức tiêu rồi còn đâu</td>\n", | |
| " <td>nói chốn mức tiêu gọi còn đâu</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>VIVOSDEV18_120</td>\n", | |
| " <td>bạn không bao giờ ra ngoài mà không dùng kem lót</td>\n", | |
| " <td>bạn không bao giờ ra ngoài mà không dùng kem lót</td>\n", | |
| " <td>bạn không bao giờ ra ngoài mà không dùng kem lót</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>VIVOSDEV13_227</td>\n", | |
| " <td>tại đây có một ông trưởng phòng nhân sự công ty</td>\n", | |
| " <td>tại đây có một ông trưởng phòng nhân sự công ty</td>\n", | |
| " <td>tại đây có một ông trưởng phòng nhân sự công ty</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>VIVOSDEV17_189</td>\n", | |
| " <td>vẫn còn nhưng bạn không dám chắc họ có hạnh phúc hay không</td>\n", | |
| " <td>vẫn còn nhưng bạn không dám chắc họ có hạnh phúc hay không</td>\n", | |
| " <td>vẫn còn nhưng bạn không dám chắt họ có hạnh phúc hay không</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>VIVOSDEV10_212</td>\n", | |
| " <td>ba mươi ba mươi mốt</td>\n", | |
| " <td>ba mươi ba mươi mốt</td>\n", | |
| " <td>ba mươi ba mươi mốt</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>VIVOSDEV18_102</td>\n", | |
| " <td>cả ngày trời không nắng gió lạnh nên thưa vắng du khách</td>\n", | |
| " <td>ngày trời không nắng gió lặn nên thưa vắng du khách</td>\n", | |
| " <td>ngày trời không nắng gió lặn nên thưa vắng du khách</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>VIVOSDEV11_129</td>\n", | |
| " <td>đi bộ leo núi đến nhừ chân</td>\n", | |
| " <td>đi bộ leo núi đến nhiều chân</td>\n", | |
| " <td>đi bộ leo nuối đến nhiều chân</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>VIVOSDEV06_139</td>\n", | |
| " <td>còn bộ khang hi từ điển</td>\n", | |
| " <td>còn bộ khăng hy từ điển</td>\n", | |
| " <td>còn bộ khăng hi từ điển</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>VIVOSDEV17_120</td>\n", | |
| " <td>sau đó bản thân học sinh phải làm đơn xin học bổng</td>\n", | |
| " <td>sau đó bản thân học sinh phải làm đơn sinh học bổng</td>\n", | |
| " <td>sau đó bản thân học sinh phải làm đơn sinh học bộng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>VIVOSDEV03_R056</td>\n", | |
| " <td>sương mù đã đọng thành những hạt giá băng</td>\n", | |
| " <td>sương mù đã động thành những hạt giá băng</td>\n", | |
| " <td>sương mùu đã động thành những hạt giá băng</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>VIVOSDEV09_039</td>\n", | |
| " <td>thịt ngọt lừ ấy lại mang theo trùng sán gây bệnh</td>\n", | |
| " <td>thịt ngọt lừ ấy lại mang trùng sáng gây bệnh</td>\n", | |
| " <td>thịt ngọt lừa ấy lại mang trùng sáng ngây bệnh</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>VIVOSDEV12_011</td>\n", | |
| " <td>đó chứng tỏ rằng chúng ta đã già</td>\n", | |
| " <td>đó chứng tỏ rằng chúng ta đã già</td>\n", | |
| " <td>đó chứng tỏ rằng chúng ta đã già</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>VIVOSDEV15_198</td>\n", | |
| " <td>nhảm nhí khi giờ học chán phèo buồn ngủ quá ờ buồn ngủ</td>\n", | |
| " <td>nhảm nhí khi giờ học chán phèo buồn ngủ quá buồn ngủ</td>\n", | |
| " <td>nhạm nhí khi giờ học trán vhèo buồn ngủ quá ờ buồn ngủ</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>VIVOSDEV08_025</td>\n", | |
| " <td>đạo diễn trẻ này có nhiều điều ngẫm ngợi về nghề</td>\n", | |
| " <td>đạo diễn trẻ này có nhiều điều ngẫm ngợi về nghề</td>\n", | |
| " <td>đạo diễn trẻ này có nhiều điều ngẫm ngợi về nghề</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>VIVOSDEV14_163</td>\n", | |
| " <td>chú bộ đội qua những câu chuyện của ông mới gần gũi làm sao</td>\n", | |
| " <td>chưa bộ đội qua những câu chuyện của ông mới gần gũi làm sao</td>\n", | |
| " <td>chưa bộ đội qua những câu chuyện của ông mới gần gũi làm sao</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>VIVOSDEV19_167</td>\n", | |
| " <td>các qui định của pháp luật không thể được ban hành theo kiểu đánh lén</td>\n", | |
| " <td>các quy định của pháp luật không thể được ban hành theo kiểu đánh lén</td>\n", | |
| " <td>các quy định của pháp luật không thể được ban hành theo kiểu đánh lén</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>VIVOSDEV11_033</td>\n", | |
| " <td>mà phải che chái ở tạm bên hông nhà cha ruột</td>\n", | |
| " <td>mà phải che trái ở tạm bên hông nhà cha ruột</td>\n", | |
| " <td>mà phải che trái ở tạm bên hông nhà cha ruột</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>VIVOSDEV06_195</td>\n", | |
| " <td>phải được thực hiện trên cơ sở</td>\n", | |
| " <td>phải được thực hiện trên cơ sở</td>\n", | |
| " <td>phải được thực hiện trên cơ sở</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>VIVOSDEV12_227</td>\n", | |
| " <td>sáu mươi sáu mươi mốt</td>\n", | |
| " <td>sáu mười sáu mười một</td>\n", | |
| " <td>sáu mười sáu mười một</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>VIVOSDEV19_020</td>\n", | |
| " <td>lên các cuộc hẹn phỏng vấn và thực hiện phỏng vấn</td>\n", | |
| " <td>lên các cuộc hẹn phỏng vấn và thực hiện phỏng vấn</td>\n", | |
| " <td>lên các cuộc hẹn phỏng vấn và thực hiện phỏng vấn</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>VIVOSDEV16_026</td>\n", | |
| " <td>cùng vợ ăn vội chén cơm thành lại lo ôn bài làm bài tập</td>\n", | |
| " <td>cùng vợ ăn vội chán cơm thành lại lo ôn bài làm bài tập</td>\n", | |
| " <td>cùng vợ ăn vộ cháng cơm thành lại lo ôm bày làm bài tập</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>VIVOSDEV15_038</td>\n", | |
| " <td>một cơ quan chính thức để khách hàng khiếu nại tham khảo và tin tưởng</td>\n", | |
| " <td>một cơ quan chính thức để khách hàng khiếu nại tham khảo và tin tưởng</td>\n", | |
| " <td>một cơ quan chính thức để khách hàng khiếu nại tham khảo và tin tưởng</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "KjxgvsH9_6W9" | |
| }, | |
| "source": [ | |
| "# Export model" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "-9XD2PfU94XI" | |
| }, | |
| "source": [ | |
| "w2v_model.save_pretrained(save_directory='./model')\n", | |
| "w2v_processor.save_pretrained(save_directory='./model')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "xlgbTGb3Aab0", | |
| "outputId": "5f51ce64-3ef3-4963-8baf-604149aae3ef" | |
| }, | |
| "source": [ | |
| "map_to_result(speech_file_to_array_fn('/content/wav2vec2-base-vietnamese-250h/t1_0001-00010.wav'))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "{'file': '/content/wav2vec2-base-vietnamese-250h/t1_0001-00010.wav',\n", | |
| " 'pred_str': 'rồi cũng hỗ trợ cho lâu lâu cũng cho gào cho này kia',\n", | |
| " 'pred_str_beam': 'rồi cũng hỗ trợ cho lâu lâu cũng cho gà cho này kia',\n", | |
| " 'sampling_rate': 16000,\n", | |
| " 'speech': array([-0.02694702, -0.03182983, -0.02288818, ..., -0.00753784,\n", | |
| " -0.01434326, -0.01483154], dtype=float32)}" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 13 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "9reALZuBFbET", | |
| "outputId": "8b8ef0a4-2540-4d9b-c8ce-0883ef9fe338" | |
| }, | |
| "source": [ | |
| "from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC\n", | |
| "from datasets import load_dataset\n", | |
| "import soundfile as sf\n", | |
| "import torch\n", | |
| "\n", | |
| "# load model and tokenizer\n", | |
| "processor = Wav2Vec2Processor.from_pretrained(\"/content/wav2vec2-base-vietnamese-250h\")\n", | |
| "model = Wav2Vec2ForCTC.from_pretrained(\"/content/wav2vec2-base-vietnamese-250h\")\n", | |
| "\n", | |
| "# define function to read in sound file\n", | |
| "def map_to_array(batch):\n", | |
| " speech, _ = sf.read(batch[\"file\"])\n", | |
| " batch[\"speech\"] = speech\n", | |
| " return batch\n", | |
| "\n", | |
| "# load dummy dataset and read soundfiles\n", | |
| "ds = map_to_array({\n", | |
| " \"file\": '/content/wav2vec2-base-vietnamese-250h/audio-test/t1_0001-00010.wav'\n", | |
| "})\n", | |
| "\n", | |
| "# tokenize\n", | |
| "input_values = processor(ds[\"speech\"], return_tensors=\"pt\", padding=\"longest\").input_values # Batch size 1\n", | |
| "\n", | |
| "# retrieve logits\n", | |
| "logits = model(input_values).logits\n", | |
| "\n", | |
| "# take argmax and decode\n", | |
| "predicted_ids = torch.argmax(logits, dim=-1)\n", | |
| "transcription = processor.batch_decode(predicted_ids)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", | |
| "It is strongly recommended to pass the ``sampling_rate`` argument to this function.Failing to do so can result in silent errors that might be hard to debug.\n" | |
| ], | |
| "name": "stderr" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 263, | |
| "referenced_widgets": [ | |
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| ] | |
| }, | |
| "id": "-ykXv2PoKBWf", | |
| "outputId": "cbcda3da-0964-4213-cd16-4fb5bca6e72e" | |
| }, | |
| "source": [ | |
| "from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC\n", | |
| "from datasets import load_dataset\n", | |
| "import soundfile as sf\n", | |
| "import torch\n", | |
| "\n", | |
| "# load model and tokenizer\n", | |
| "processor = Wav2Vec2Processor.from_pretrained(\"nguyenvulebinh/wav2vec2-base-vietnamese-250h\")\n", | |
| "model = Wav2Vec2ForCTC.from_pretrained(\"nguyenvulebinh/wav2vec2-base-vietnamese-250h\")\n", | |
| "\n", | |
| "# define function to read in sound file\n", | |
| "def map_to_array(batch):\n", | |
| " speech, _ = sf.read(batch[\"file\"])\n", | |
| " batch[\"speech\"] = speech\n", | |
| " return batch\n", | |
| "\n", | |
| "# load dummy dataset and read soundfiles\n", | |
| "ds = map_to_array({\n", | |
| " \"file\": '/content/wav2vec2-base-vietnamese-250h/audio-test/t1_0001-00010.wav'\n", | |
| "})\n", | |
| "\n", | |
| "# tokenize\n", | |
| "input_values = processor(ds[\"speech\"], return_tensors=\"pt\", padding=\"longest\").input_values # Batch size 1\n", | |
| "\n", | |
| "# retrieve logits\n", | |
| "logits = model(input_values).logits\n", | |
| "\n", | |
| "# take argmax and decode\n", | |
| "predicted_ids = torch.argmax(logits, dim=-1)\n", | |
| "transcription = processor.batch_decode(predicted_ids)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
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| }, | |
| "text/plain": [ | |
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| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
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| { | |
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| }, | |
| { | |
| "output_type": "display_data", | |
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| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" | |
| ], | |
| "name": "stderr" | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.jupyter.widget-view+json": { | |
| "model_id": "32ac0964bad14718a064e1303cb76f59", | |
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| }, | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "It is strongly recommended to pass the ``sampling_rate`` argument to this function.Failing to do so can result in silent errors that might be hard to debug.\n" | |
| ], | |
| "name": "stderr" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "ZB94tX3LKFbd", | |
| "outputId": "795f1e77-a71c-4bcd-c959-5971f1696bff" | |
| }, | |
| "source": [ | |
| "transcription" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "['rồi cũng hỗ trợ cho lâu lâu cũng cho gào cho này kia']" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 27 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "lGnxez8SMrwR" | |
| }, | |
| "source": [], | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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