{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "an4_asr_train.ipynb", "version": "0.3.2", "provenance": [], "collapsed_sections": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "accelerator": "GPU" }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "qncY3FktdgMI", "colab_type": "text" }, "source": [ "# Speech Recognition (Library)\n", "\n", "This example shows you a practical ASR example using ESPnet as a command line interface and library.\n", "\n", "See also\n", "\n", "- run in [colab](https://colab.research.google.com/github/espnet/notebook/blob/master/asr_library.ipynb)\n", "- documetation https://espnet.github.io/espnet/\n", "- github https://github.com/espnet\n", "\n", "Author: [Shigeki Karita](https://github.com/ShigekiKarita)\n", "\n", "## Installation\n", "\n", "ESPnet depends on Kaldi ASR toolkit and Warp-CTC. This cell will take a few minutes." ] }, { "cell_type": "code", "metadata": { "id": "mLxx6gVHwda6", "colab_type": "code", "colab": {} }, "source": [ "# TODO(karita): put these lines in ./espnet/tools/setup_colab.sh\n", "# OS setup\n", "!sudo apt-get install bc tree\n", "!cat /etc/os-release\n", "\n", "# espnet setup\n", "!git clone https://github.com/espnet/espnet\n", "!cd espnet; pip install -e .\n", "!mkdir espnet/tools/venv/bin; touch espnet/tools/venv/bin/activate\n", "\n", "# warp ctc setup\n", "!git clone https://github.com/espnet/warp-ctc -b pytorch-1.1\n", "!cd warp-ctc && mkdir build && cd build && cmake .. && make -j4\n", "!cd warp-ctc/pytorch_binding && python setup.py install \n", "\n", "# kaldi setup\n", "!cd ./espnet/tools; git clone https://github.com/kaldi-asr/kaldi\n", "!echo \"\" > ./espnet/tools/kaldi/tools/extras/check_dependencies.sh # ignore check\n", "!chmod +x ./espnet/tools/kaldi/tools/extras/check_dependencies.sh\n", "!cd ./espnet/tools/kaldi/tools; make sph2pipe sclite\n", "!rm -rf espnet/tools/kaldi/tools/python\n", "![ ! -e ubuntu16-featbin.tar.gz ] && wget https://18-198329952-gh.circle-artifacts.com/0/home/circleci/repo/ubuntu16-featbin.tar.gz\n", "!tar -xf ./ubuntu16-featbin.tar.gz\n", "!cp featbin/* espnet/tools/kaldi/src/featbin/" ], "execution_count": 0, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "_6pH9DX1hTLj", "colab_type": "text" }, "source": [ "## ESPnet data preparation\n", "\n", "You can use the end-to-end script `run.sh` for reproducing systems reported in `espnet/egs/*/asr1/RESULTS.md`. Typically, we organize `run.sh` with several stages:\n", "\n", "0. Data download (if available)\n", "1. Kaldi-style data preparation \n", "2. Dump useful data for traning (e.g., JSON, HDF5, etc)\n", "3. Lanuage model training\n", "4. ASR model training\n", "5. Decoding and evaluation\n", "\n", "For example, if you add `--stop-stage 2`, you can stop the script before neural network training." ] }, { "cell_type": "code", "metadata": { "id": "YMMmYjCDBtSm", "colab_type": "code", "colab": {} }, "source": [ "!cd espnet/egs/an4/asr1; ./run.sh --ngpu 1 --stop-stage 2" ], "execution_count": 0, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "A_ATcz0jnCcF", "colab_type": "text" }, "source": [ "## Kaldi-style directories\n", "\n", "Always we organize each recipe placed in `egs/xxx/asr1` in Kaldi way. For example, the important directories are:\n", "\n", "- `conf/`: kaldi configurations, e.g., speech feature\n", "- `data/`: almost raw [data prepared by Kaldi](https://kaldi-asr.org/doc/data_prep.html)\n", "- `exp/`: intermidiate files through experiments, e.g., log files, model parameters\n", "- `fbank/`: speech feature binary files, e.g., [ark, scp](https://kaldi-asr.org/doc/io.html)\n", "- `dump/`: ESPnet meta data for tranining, e.g., json, hdf5\n", "- `local/`: corpus specific data preparation scripts\n", "- [steps/](https://github.com/kaldi-asr/kaldi/tree/master/egs/wsj/s5/steps), [utils/](https://github.com/kaldi-asr/kaldi/tree/master/egs/wsj/s5/utils): Kaldi's helper scripts" ] }, { "cell_type": "code", "metadata": { "id": "gsVAFRyNmr_h", "colab_type": "code", "outputId": "0c254581-1121-482c-87f8-f4535af0a144", "colab": { "base_uri": "https://localhost:8080/", "height": 173 } }, "source": [ "!tree -L 1\n", "!ls data/train" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ ".\n", "├── espnet\n", "├── featbin\n", "├── sample_data\n", "├── ubuntu16-featbin.tar.gz\n", "└── warp-ctc\n", "\n", "4 directories, 1 file\n", "ls: cannot access 'data/train': No such file or directory\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "u6lxhnHtjKv3", "colab_type": "text" }, "source": [ "## ESPnet as a library\n", "\n", "Here we use ESPnet as a library to create a simple Python snippet for speech recognition. ESPnet 's training script'`asr_train.py` has three parts:\n", "\n", "1. Load train/dev dataset\n", "2. Create minibatches\n", "3. Build neural networks\n", "4. Update neural networks by iterating datasets\n", "\n", "Let's implement these procedures from scratch!\n", "\n", "### Load train/dev dataset (1/4)\n", "\n", "First, we will check how `run.sh` organized the JSON files and load the pair of the speech feature and its transcription." ] }, { "cell_type": "code", "metadata": { "id": "BIviLgGKNAyk", "colab_type": "code", "outputId": "dff406d8-b805-4e1a-d9b9-c4140c6539b2", "colab": { "base_uri": "https://localhost:8080/", "height": 459 } }, "source": [ "import json\n", "import matplotlib.pyplot as plt\n", "import kaldiio\n", "\n", "root = \"espnet/egs/an4/asr1\"\n", "with open(root + \"/dump/train_nodev/deltafalse/data.json\", \"r\") as f:\n", " train_json = json.load(f)[\"utts\"]\n", "with open(root + \"/dump/train_dev/deltafalse/data.json\", \"r\") as f:\n", " dev_json = json.load(f)[\"utts\"]\n", " \n", "# the first training data for speech recognition\n", "key, info = next(iter(train_json.items()))\n", "\n", "# plot the 80-dim fbank + 3-dim pitch speech feature\n", "fbank = kaldiio.load_mat(info[\"input\"][0][\"feat\"])\n", "plt.matshow(fbank.T[::-1])\n", "plt.title(key + \": \" + info[\"output\"][0][\"text\"])\n", "\n", "# print the key-value pair\n", "key, info" ], "execution_count": 2, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "('fkai-an311-b',\n", " {'input': [{'feat': '/content/espnet/egs/an4/asr1/dump/train_nodev/deltafalse/feats.1.ark:13',\n", " 'name': 'input1',\n", " 'shape': [308, 83]}],\n", " 'output': [{'name': 'target1',\n", " 'shape': [26, 30],\n", " 'text': 'ERASE I S L F THIRTY EIGHT',\n", " 'token': 'E R A S E I S L F T H I R T Y E I G H T',\n", " 'tokenid': '7 20 3 21 7 2 11 2 21 2 14 2 8 2 22 10 11 20 22 27 2 7 11 9 10 22'}],\n", " 'utt2spk': 'fkai'})" ] }, "metadata": { "tags": [] }, "execution_count": 2 }, { "output_type": "display_data", "data": { "image/png": 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zHR2sG17G9VXmHt09yvkyPLHKfMhfO7qv/f0fPnB/+3t5vcn33gtzfe7t5vq2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AKB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\nQmCC\n", "text/plain": [ "
" ] }, "metadata": { "tags": [] } } ] }, { "cell_type": "markdown", "metadata": { "id": "sz9A5Y6tlOLh", "colab_type": "text" }, "source": [ "### Create minibatches (2/4)\n", "\n", "To parallelize neural network training, we create minibatches that containes several sequence pairs by splitting datasets." ] }, { "cell_type": "code", "metadata": { "id": "iNuH7JYRkWFO", "colab_type": "code", "outputId": "b90a59a9-839a-4a0d-a73d-eafe6bd43acd", "colab": { "base_uri": "https://localhost:8080/", "height": 538 } }, "source": [ "from espnet.utils.training.batchfy import make_batchset\n", "\n", "batch_size = 32\n", "trainset = make_batchset(train_json, batch_size)\n", "devset = make_batchset(dev_json, batch_size)\n", "assert len(devset[0]) == batch_size\n", "devset[0][:3]" ], "execution_count": 3, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "[('fbbh-an89-b',\n", " {'input': [{'feat': '/content/espnet/egs/an4/asr1/dump/train_dev/deltafalse/feats.1.ark:257878',\n", " 'name': 'input1',\n", " 'shape': [638, 83]}],\n", " 'output': [{'name': 'target1',\n", " 'shape': [40, 30],\n", " 'text': 'RUBOUT T G J W B SEVENTY NINE FIFTY NINE',\n", " 'token': 'R U B O U T T G J W B S E V E N T Y N I N E F I F T Y N I N E',\n", " 'tokenid': '20 23 4 17 23 22 2 22 2 9 2 12 2 25 2 4 2 21 7 24 7 16 22 27 2 16 11 16 7 2 8 11 8 22 27 2 16 11 16 7'}],\n", " 'utt2spk': 'fbbh'}),\n", " ('fejs-cen4-b',\n", " {'input': [{'feat': '/content/espnet/egs/an4/asr1/dump/train_dev/deltafalse/feats.4.ark:106716',\n", " 'name': 'input1',\n", " 'shape': [528, 83]}],\n", " 'output': [{'name': 'target1',\n", " 'shape': [23, 30],\n", " 'text': 'F I N D L E Y D R I V E',\n", " 'token': 'F I N D L E Y D R I V E',\n", " 'tokenid': '8 2 11 2 16 2 6 2 14 2 7 2 27 2 6 2 20 2 11 2 24 2 7'}],\n", " 'utt2spk': 'fejs'}),\n", " ('ffmm-cen2-b',\n", " {'input': [{'feat': '/content/espnet/egs/an4/asr1/dump/train_dev/deltafalse/feats.5.ark:52535',\n", " 'name': 'input1',\n", " 'shape': [498, 83]}],\n", " 'output': [{'name': 'target1',\n", " 'shape': [21, 30],\n", " 'text': 'F R A N C E S M A R Y',\n", " 'token': 'F R A N C E S M A R Y',\n", " 'tokenid': '8 2 20 2 3 2 16 2 5 2 7 2 21 2 15 2 3 2 20 2 27'}],\n", " 'utt2spk': 'ffmm'})]" ] }, "metadata": { "tags": [] }, "execution_count": 3 } ] }, { "cell_type": "markdown", "metadata": { "id": "vxrU2nSdtfvU", "colab_type": "text" }, "source": [ "### Build neural networks (3/4)\n", "\n", "For simplicity, we use a predefined model: [Transformer](https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf). \n", "\n", "NOTE: You can also use your custom model in command line tools as `asr_train.py --model-module your_module:YourModel`" ] }, { "cell_type": "code", "metadata": { "id": "lD_IpX0fg-yj", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 764 }, "outputId": "5fcca1f6-0d7a-401d-e92b-c4226a76dde0" }, "source": [ "import argparse\n", "from espnet.bin.asr_train import get_parser\n", "from espnet.nets.pytorch_backend.e2e_asr import E2E\n", "\n", "parser = get_parser()\n", "parser = E2E.add_arguments(parser)\n", "config = parser.parse_args([\n", " \"--mtlalpha\", \"0.0\", # weight for cross entropy and CTC loss\n", " \"--outdir\", \"out\", \"--dict\", \"\"]) # TODO: allow no arg\n", "\n", "idim = info[\"input\"][0][\"shape\"][1]\n", "odim = info[\"output\"][0][\"shape\"][1]\n", "setattr(config, \"char_list\", [])\n", "model = E2E(idim, odim, config)\n", "model" ], "execution_count": 5, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "E2E(\n", " (enc): Encoder(\n", " (enc): ModuleList(\n", " (0): RNNP(\n", " (birnn0): LSTM(83, 300, batch_first=True, bidirectional=True)\n", " (bt0): Linear(in_features=600, out_features=320, bias=True)\n", " (birnn1): LSTM(320, 300, batch_first=True, bidirectional=True)\n", " (bt1): Linear(in_features=600, out_features=320, bias=True)\n", " (birnn2): LSTM(320, 300, batch_first=True, bidirectional=True)\n", " (bt2): Linear(in_features=600, out_features=320, bias=True)\n", " (birnn3): LSTM(320, 300, batch_first=True, bidirectional=True)\n", " (bt3): Linear(in_features=600, out_features=320, bias=True)\n", " )\n", " )\n", " )\n", " (ctc): CTC(\n", " (ctc_lo): Linear(in_features=320, out_features=30, bias=True)\n", " (ctc_loss): CTCLoss()\n", " )\n", " (att): ModuleList(\n", " (0): AttDot(\n", " (mlp_enc): Linear(in_features=320, out_features=320, bias=True)\n", " (mlp_dec): Linear(in_features=320, out_features=320, bias=True)\n", " )\n", " )\n", " (dec): Decoder(\n", " (embed): Embedding(30, 320)\n", " (dropout_emb): Dropout(p=0.0)\n", " (decoder): ModuleList(\n", " (0): LSTMCell(640, 320)\n", " )\n", " (dropout_dec): ModuleList(\n", " (0): Dropout(p=0.0)\n", " )\n", " (output): Linear(in_features=320, out_features=30, bias=True)\n", " (att): ModuleList(\n", " (0): AttDot(\n", " (mlp_enc): Linear(in_features=320, out_features=320, bias=True)\n", " (mlp_dec): Linear(in_features=320, out_features=320, bias=True)\n", " )\n", " )\n", " )\n", ")" ] }, "metadata": { "tags": [] }, "execution_count": 5 } ] }, { "cell_type": "markdown", "metadata": { "id": "jlR2zeugwYYS", "colab_type": "text" }, "source": [ "### Update neural networks by iterating datasets (4/4)\n", "\n", "Finaly, we got the training part." ] }, { "cell_type": "code", "metadata": { "id": "kAwPXLb-rPjm", "colab_type": "code", "outputId": "6881e4be-f1bc-47f3-d43b-33a37aab74e4", "colab": { "base_uri": "https://localhost:8080/", "height": 191 } }, "source": [ "import numpy\n", "import torch\n", "from torch.nn.utils.rnn import pad_sequence\n", "from torch.nn.utils.clip_grad import clip_grad_norm_\n", "from torch.utils.data import DataLoader\n", "\n", "def collate(minibatch):\n", " fbanks = []\n", " tokens = []\n", " for key, info in minibatch[0]:\n", " fbanks.append(torch.tensor(kaldiio.load_mat(info[\"input\"][0][\"feat\"])))\n", " tokens.append(torch.tensor([int(s) for s in info[\"output\"][0][\"tokenid\"].split()]))\n", " ilens = torch.tensor([x.shape[0] for x in fbanks])\n", " return pad_sequence(fbanks, batch_first=True), ilens, pad_sequence(tokens, batch_first=True)\n", "\n", "train_loader = DataLoader(trainset, collate_fn=collate, shuffle=True, pin_memory=True)\n", "dev_loader = DataLoader(devset, collate_fn=collate, pin_memory=True)\n", "model.cuda()\n", "optim = torch.optim.Adam(model.parameters(), lr=0.001, betas=(0.9, 0.98))\n", "\n", "n_iter = len(trainset)\n", "n_epoch = 10\n", "total_iter = n_iter * n_epoch\n", "train_acc = []\n", "valid_acc = []\n", "for epoch in range(n_epoch):\n", " # training\n", " acc = []\n", " model.train()\n", " for data in train_loader:\n", " loss = model(*[d.cuda() for d in data])\n", " optim.zero_grad()\n", " loss.backward()\n", " acc.append(model.acc)\n", " norm = clip_grad_norm_(model.parameters(), 10.0)\n", " optim.step()\n", " train_acc.append(numpy.mean(acc))\n", "\n", " # validation\n", " acc = []\n", " model.eval()\n", " for data in dev_loader:\n", " model(*[d.cuda() for d in data])\n", " acc.append(model.acc)\n", " valid_acc.append(numpy.mean(acc))\n", " print(f\"epoch: {epoch}, train acc: {train_acc[-1]:.3f}, dev acc: {valid_acc[-1]:.3f}\")\n" ], "execution_count": 7, "outputs": [ { "output_type": "stream", "text": [ "epoch: 0, train acc: 0.566, dev acc: 0.577\n", "epoch: 1, train acc: 0.715, dev acc: 0.636\n", "epoch: 2, train acc: 0.750, dev acc: 0.686\n", "epoch: 3, train acc: 0.774, dev acc: 0.684\n", "epoch: 4, train acc: 0.778, dev acc: 0.703\n", "epoch: 5, train acc: 0.795, dev acc: 0.739\n", "epoch: 6, train acc: 0.796, dev acc: 0.745\n", "epoch: 7, train acc: 0.801, dev acc: 0.757\n", "epoch: 8, train acc: 0.807, dev acc: 0.746\n", "epoch: 9, train acc: 0.814, dev acc: 0.756\n" ], "name": "stdout" } ] }, { "cell_type": "code", "metadata": { "id": "zoYq9dsw1EQO", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 286 }, "outputId": "4cac3e17-0f70-4daa-dd69-0b8333765691" }, "source": [ "import matplotlib.pyplot as plt\n", "\n", "plt.plot(range(len(train_acc)), train_acc, label=\"train acc\")\n", "plt.plot(range(len(valid_acc)), valid_acc, label=\"dev acc\")\n", "plt.grid()\n", "plt.legend()" ], "execution_count": 8, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": { "tags": [] }, "execution_count": 8 }, { "output_type": "display_data", "data": { "image/png": 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" ] }, "metadata": { "tags": [] } } ] }, { "cell_type": "code", "metadata": { "id": "jhqpa-BH_G8t", "colab_type": "code", "colab": {} }, "source": [ "torch.save(model.state_dict(), \"best.pt\")" ], "execution_count": 0, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "2TA5RO6rVzlr", "colab_type": "text" }, "source": [ "### Recognize speech" ] }, { "cell_type": "code", "metadata": { "id": "Et9tvO1gVvo4", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 320 }, "outputId": "ddcc4efd-9938-4c8d-b8cb-90a2f117575b" }, "source": [ "import json\n", "import matplotlib.pyplot as plt\n", "import kaldiio\n", "from espnet.bin.asr_recog import get_parser\n", "\n", "# load data\n", "root = \"espnet/egs/an4/asr1\"\n", "with open(root + \"/dump/test/deltafalse/data.json\", \"r\") as f:\n", " test_json = json.load(f)[\"utts\"]\n", " \n", "key, info = list(test_json.items())[10]\n", "\n", "# plot the 80-dim fbank + 3-dim pitch speech feature\n", "fbank = kaldiio.load_mat(info[\"input\"][0][\"feat\"])\n", "plt.matshow(fbank.T[::-1])\n", "plt.title(key + \": \" + info[\"output\"][0][\"text\"])\n", "\n", "# load token dict\n", "with open(root + \"/data/lang_1char/train_nodev_units.txt\", \"r\") as f:\n", " token_list = [entry.split()[0] for entry in f]\n", "token_list.insert(0, '')\n", "token_list.append('')\n", "\n", "# recognize speech\n", "parser = get_parser()\n", "args = parser.parse_args([\n", " \"--beam-size\", \"1\",\n", " \"--ctc-weight\", \"0\",\n", " \"--result-label\", \"out.json\",\n", " \"--model\", \"\"\n", "])\n", "model.cpu()\n", "model.eval()\n", "\n", "def to_str(result):\n", " return \"\".join(token_list[y] for y in result[0][\"yseq\"]) \\\n", " .replace(\"\", \"\").replace(\"\", \" \").replace(\"\", \"\")\n", "\n", "print(\"groundtruth:\", info[\"output\"][0][\"text\"])\n", "print(\"prediction: \", to_str(model.recognize(fbank, args, token_list)))" ], "execution_count": 16, "outputs": [ { "output_type": "stream", "text": [ "groundtruth: ONE FIVE TWO THREE SIX\n", "prediction: ONE FIVE TWO ONE THREE TWO ONE THREE\n" ], "name": "stdout" }, { "output_type": "display_data", "data": { "image/png": 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Q7VaquLOdIDc3RWX8lwdfWG9fOJHacHE+TP4nHgCt+bZ0XXUibPPZSQU8VZZi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\nQ5pS8wwtfaS2SeoBsYkUmAAq4GAA+kmk61BdaTMC3bHUyS0d3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