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  "cells": [
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      "cell_type": "markdown",
      "metadata": {
        "id": "elK2Q3YHALZc"
      },
      "source": [
        "# Практика №2\n",
        "\n",
        "На прошлой практике мы реализовали DTW алгоритм. Он очень хорош и вроде как даже где-то применяется. Но у него есть существенные недостатки:\n",
        "\n",
        "1) Для распознавания какого-либо слова необходимо иметь заранее подготовленные эталонные записи. Из этого вытекает проблема масштабирования системы с большим словарем.<br>\n",
        "2) Подобная система имеет плохую устойчивость к шумам.<br>\n",
        "3) По какому принципу вибирать нужные эталоны?<br>\n",
        "4) Сколько должно быть таких эталонов, чтобы покрыть всю вариативность произнесеней?<br>\n",
        "5) Чем больше эталонов, тем алгоритм вычислительнозатратен.<br>\n",
        "\n",
        "В этом уроке мы перейдем от DTW к распознаванию по эталонному словарю. \n",
        "\n",
        "Эталон в графе теперь будет задаваться как последовательность фонем из словаря. Словарь для YES_NO (data/lexicon_yes_no.txt) выглядит следующим образом:\n",
        "\n",
        "<b>YES</b>  SIL Y EH1 S SIL<br>\n",
        "<b>NO</b>  SIL N OW1 SIL<br>\n",
        "\n",
        "Словарь для цифр (data/lexicon_digits.txt):\n",
        "\n",
        "<b>ZERO</b>  SIL Z IH1 R OW0 SIL<br>\n",
        "<b>ZERO</b>  SIL Z IY1 R OW0 SIL<br>\n",
        "<b>ONE</b>  SIL W AH1 N SIL<br>\n",
        "<b>ONE</b>  SIL HH W AH1 N SIL<br>\n",
        "<b>TWO</b>  SIL T UW1 SIL<br>\n",
        "<b>THREE</b>  SIL TH R IY1 SIL<br>\n",
        "<b>FOUR</b>  SIL F AO1 R SIL<br>\n",
        "<b>FIVE</b>  SIL F AY1 V SIL<br>\n",
        "<b>SIX</b>  SIL S IH1 K S SIL<br>\n",
        "<b>SEVEN</b>  SIL S EH1 V AH0 N SIL<br>\n",
        "<b>EIGHT</b>  SIL EY1 T SIL<br>\n",
        "<b>NINE</b>  SIL N AY1 N SIL<br>\n",
        "\n",
        "SIL здесь – это фонема паузы.\n",
        "Как вы возможно заметили, для некторых слов имеется несколько вариантов фонемной транскрипции. Это позволяет лучше учесть фонетическое разнообразие в произнесении некоторых слов.\n",
        "\n",
        "Каждой фонеме будет сопоставлен наиболее типичный для нее вектор признаков. В данном случае мы будем использовать среднее значение вектора признаков фонем, взятых из обучающего набора. Будем называть это акустической моделью."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PjAjWp16ALjb"
      },
      "source": [
        "### Данные для обучения\n",
        "\n",
        "Наша задача собрать статистику акустических признаков по каждой фонеме, находящейся в графе распознавания. В качестве обучающей выборки мы будем использовать подмножество данных librispeech (аудиозаписи чтения книг на английском). Для этого предварительно мной была получена покадровая разметка этого подмножества на фонемы. Схематично данный процесс представлен на картинке ниже:\n",
        "\n",
        "![](https://drive.google.com/uc?export=view&id=16PdwggV_Cl6aaD4cu1MZ-fKzWzAvcFVw)\n",
        "\n",
        "Файл разметки (ali_phones.txt) представлен в формате:\n",
        "\n",
        "<b>filename1 phone_frame1 phone_frame2 phone_frame3 ...<br>\n",
        "   filename2 phone_frame1 phone_frame2 phone_frame3 ...</b> \n",
        "   \n",
        "Пример такой покадровой фонемной разметки одного файла с текстом \"<b>MUCH COULD BE DONE IN THREE YEARS</b>\" представлен ниже:\n",
        "\n",
        "<b>1183-124566-0003 SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL M M M M M M M M M AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 CH CH CH CH CH CH CH CH CH CH CH K K K K\n",
        "K K K K K UH1 UH1 UH1 UH1 D D D D D B B B B B B IY0 IY0 IY0 IY0 IY0 D D D D D D D D D D D D AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 AH1 N N\n",
        "N N N N N N N N N N N N N SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SIL SI\n",
        "L SIL SIL SIL SIL SIL SIL SIL SIL IH1 IH1 IH1 IH1 IH1 IH1 IH1 IH1 IH1 IH1 IH1 N N N N N N N N N N SIL SIL SIL SIL SIL TH TH TH TH TH TH TH TH TH TH TH TH TH R R R R R R IY1 IY1\n",
        " IY1 IY1 IY1 IY1 IY1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y IH1 IH1 IH1 IH1 IH1 IH1 IH1 IH1 R R R R R R R R R R R R R R R Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z SIL SIL SIL SIL</b>\n",
        " \n",
        "Аудио файлы этих данных лежат в папке \"data/train_librispeech_10h/wav_dir\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3aDoHq5vA3BE"
      },
      "source": [
        "### Bootstrap"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p-aUbl81_LC2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9067561f-8cb5-4b81-fb55-ec0e82b8b3cc"
      },
      "source": [
        "!pip install --upgrade --no-cache-dir gdown\n",
        "\n",
        "!gdown --id '1meikF0XqBUnVZKoY3160MQ0R25lq-EMu'\n",
        "!gdown --id '1f0LkW6I3Q5CnOThuNFAJ9umgnb2eU4Ox'"
      ],
      "execution_count": 1,
      "outputs": [
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          "name": "stdout",
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            "/usr/local/lib/python3.7/dist-packages/gdown/cli.py:131: FutureWarning: Option `--id` was deprecated in version 4.3.1 and will be removed in 5.0. You don't need to pass it anymore to use a file ID.\n",
            "  category=FutureWarning,\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1meikF0XqBUnVZKoY3160MQ0R25lq-EMu\n",
            "To: /content/lab2.zip\n",
            "100% 1.66M/1.66M [00:00<00:00, 88.1MB/s]\n",
            "/usr/local/lib/python3.7/dist-packages/gdown/cli.py:131: FutureWarning: Option `--id` was deprecated in version 4.3.1 and will be removed in 5.0. You don't need to pass it anymore to use a file ID.\n",
            "  category=FutureWarning,\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1f0LkW6I3Q5CnOThuNFAJ9umgnb2eU4Ox\n",
            "To: /content/train_librispeech_10h.zip\n",
            "100% 679M/679M [00:06<00:00, 105MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NT6a5YIEBD9Y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "79b586a6-93f4-467b-c0da-1c1f95386ced"
      },
      "source": [
        "!unzip -q lab2.zip\n",
        "!unzip -q train_librispeech_10h.zip\n",
        "!mv train_librispeech_10h lab2/data\n",
        "!rm -rf lab2.zip sample_data train_librispeech_10h.zip\n",
        "%cd lab2"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/lab2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bbuT2aOeEnFP"
      },
      "source": [
        "import os\n",
        "import numpy as np\n",
        "import time\n",
        "from tqdm.notebook import tqdm\n",
        "import matplotlib.pyplot as plt\n",
        "import IPython.display as ipd\n",
        "import librosa, librosa.display\n",
        "\n",
        "from sklearn.mixture import GaussianMixture\n",
        "from sklearn.manifold import TSNE\n",
        "\n",
        "%matplotlib inline\n",
        "plt.rcParams['figure.figsize'] = (15.0, 5.0)\n",
        "plt.rcParams['image.interpolation'] = 'nearest'\n",
        "plt.rcParams['image.cmap'] = 'gray'"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yK0OtyHPEoH_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 127
        },
        "outputId": "94f63a23-ad28-49df-e004-2005f47333b1"
      },
      "source": [
        "# рассмотрим пример такой записи:\n",
        "wav_example = 'data/train_librispeech_10h/wav_dir/1183-124566-0003.flac'\n",
        "\n",
        "# чтение wav файла:\n",
        "x, sr = librosa.load(wav_example, sr=None)     # sr=None to preserve the native sampling rate\n",
        "\n",
        "print(f'Number of samples: {len(x)}')\n",
        "print(f'Sampling rate: {sr} Hz')\n",
        "print(f'Duration: {len(x)/sr:.2f} s')  # ~ librosa.get_duration(x, sr)\n",
        "\n",
        "# воспроизведение:\n",
        "ipd.Audio(x, rate=sr)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of samples: 45680\n",
            "Sampling rate: 16000 Hz\n",
            "Duration: 2.85 s\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C2tGLWBmEssy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "outputId": "2a6c32ba-9314-4fe6-983e-d5eaa1ebfdd1"
      },
      "source": [
        "# спектрограмма:\n",
        "D = librosa.amplitude_to_db(np.abs(librosa.stft(x)), ref=np.max)\n",
        "plt.figure(figsize=(15,5))\n",
        "librosa.display.specshow(D, sr=sr, y_axis='hz', x_axis='time')\n",
        "plt.colorbar(format='%+2.0f dB')\n",
        "plt.title('Log-frequency power spectrogram')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Log-frequency power spectrogram')"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JXFxvv-_E8t8"
      },
      "source": [
        "### Подготовка данных"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ku1F2BULE6Xe"
      },
      "source": [
        "# загрузка покадровой фонемной разметки в словарь:\n",
        "def load_phone_aligment(aligment_file):\n",
        "    ali_dict = {}\n",
        "    with open(aligment_file, encoding='utf-8') as fn:\n",
        "        for line in fn:\n",
        "            line = line.strip().split()\n",
        "            ali_dict[line[0]] = line[1:]\n",
        "    return ali_dict\n",
        "\n",
        "ali_file = 'data/train_librispeech_10h/ali_phones.txt'\n",
        "ali_dict = load_phone_aligment(ali_file)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3uAVnRPDE_MS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "e29510ab35f046d7a6e87bf52d6683f0",
            "e4d39dc3c8a840e6be8ee8a5046292b0",
            "3a330197c4fe4f02bb8c96c06677018c",
            "33efdf88ce9344d2ab7e12cf0fa4899c",
            "daa8d0c67c034de5b6cca4a7466796ef",
            "e3c3490e16f8453da578a96e179c072e",
            "c46740159f2f4f198fa414e33aef9570",
            "b835a5b252c7457f8a5d2a0bc13d7293",
            "5af9cf577072403a8489d348908c721a",
            "36dc7867223f48949160b0f2b1eca1c6",
            "730b6a8c84b8474b8f0c8ca731f6a15f"
          ]
        },
        "outputId": "0a1be3f2-fe16-40cb-ad44-6cb3f42b4ad3"
      },
      "source": [
        "# подсчет акустиеских признаков для записей из папки:\n",
        "def load_data_dict(dir_path, count=None):\n",
        "    data_dict = {}\n",
        "    for step, wav_name in tqdm(enumerate(os.listdir(dir_path))):\n",
        "        x, sr = librosa.load(os.path.join(dir_path, wav_name), sr=None) \n",
        "        mfcc = librosa.feature.mfcc(x,\n",
        "                                    sr=sr,\n",
        "                                    n_mfcc=13, \n",
        "                                    n_fft=int(sr * 0.025),\n",
        "                                    hop_length=int(sr * 0.01))\n",
        "        if count and step == count:\n",
        "            print(f'Early stop at {step}th file..')\n",
        "            break\n",
        "        data_dict[wav_name.split('.')[0]] = mfcc.T  \n",
        "    return data_dict\n",
        "\n",
        "train_records_dir = 'data/train_librispeech_10h/wav_dir'\n",
        "train_data_dict = load_data_dict(train_records_dir, count=100)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e29510ab35f046d7a6e87bf52d6683f0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Early stop at 100th file..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CN2Q0wYTFMs5"
      },
      "source": [
        "# инициализация списка допустимых фонем из предустановленного файла\n",
        "def init_phones_dict(phones_file):\n",
        "    phones_dict = {}\n",
        "    with open(phones_file, encoding='utf-8') as fn:\n",
        "        for line in fn:\n",
        "            phones_dict[line.strip()] = []\n",
        "    return phones_dict\n",
        "\n",
        "phones_file = 'data/train_librispeech_10h/phones'\n",
        "phones_dict = init_phones_dict(phones_file)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Yd0anSjFOr_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "686c73d5-9462-4d41-f626-4597009a7965"
      },
      "source": [
        "# присвоим каждой фонеме набор ее признаков в соответствии с фонемной разметкой обучающей выборки\n",
        "# количество кадров признаков может немного отличаться от количества размеченных фонем\n",
        "# это связано с особенностми построения разметки в Kaldi\n",
        "for file_name in train_data_dict.keys():\n",
        "    file_feats = train_data_dict[file_name]\n",
        "    file_ali = ali_dict[file_name]\n",
        "    for frame in range(min(len(file_feats), len(file_ali))):\n",
        "        phones_dict[file_ali[frame]].append(file_feats[frame])\n",
        "        \n",
        "# выведем статистику по кадой фонеме (некоторые фонемы вообще не используются, это особенности разметки в Kaldi):\n",
        "count = 0\n",
        "for phone in phones_dict.keys():\n",
        "    if len(phones_dict[phone]) == 0:\n",
        "        count +=1\n",
        "    print(f'{phone:<3}: {len(phones_dict[phone])}')\n",
        "print(f'Number of empty phones is: {count}')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SIL: 23073\n",
            "SPN: 955\n",
            "AA : 0\n",
            "AA0: 36\n",
            "AA1: 1551\n",
            "AA2: 91\n",
            "AE : 0\n",
            "AE0: 38\n",
            "AE1: 3343\n",
            "AE2: 73\n",
            "AH : 0\n",
            "AH0: 5196\n",
            "AH1: 1665\n",
            "AH2: 54\n",
            "AO : 0\n",
            "AO0: 16\n",
            "AO1: 1605\n",
            "AO2: 53\n",
            "AW : 0\n",
            "AW0: 0\n",
            "AW1: 1206\n",
            "AW2: 69\n",
            "AY : 0\n",
            "AY0: 12\n",
            "AY1: 3370\n",
            "AY2: 156\n",
            "B  : 1569\n",
            "CH : 944\n",
            "D  : 3601\n",
            "DH : 2010\n",
            "EH : 0\n",
            "EH0: 36\n",
            "EH1: 2726\n",
            "EH2: 79\n",
            "ER : 0\n",
            "ER0: 2363\n",
            "ER1: 868\n",
            "ER2: 9\n",
            "EY : 0\n",
            "EY0: 13\n",
            "EY1: 2501\n",
            "EY2: 107\n",
            "F  : 2232\n",
            "G  : 728\n",
            "HH : 2160\n",
            "IH : 0\n",
            "IH0: 2683\n",
            "IH1: 2185\n",
            "IH2: 106\n",
            "IY : 0\n",
            "IY0: 2207\n",
            "IY1: 2290\n",
            "IY2: 48\n",
            "JH : 625\n",
            "K  : 2770\n",
            "L  : 4089\n",
            "M  : 2733\n",
            "N  : 5605\n",
            "NG : 1458\n",
            "OW : 0\n",
            "OW0: 167\n",
            "OW1: 1875\n",
            "OW2: 275\n",
            "OY : 0\n",
            "OY0: 0\n",
            "OY1: 331\n",
            "OY2: 0\n",
            "P  : 2371\n",
            "R  : 3733\n",
            "S  : 6445\n",
            "SH : 1042\n",
            "T  : 5861\n",
            "TH : 756\n",
            "UH : 0\n",
            "UH0: 5\n",
            "UH1: 358\n",
            "UH2: 7\n",
            "UW : 0\n",
            "UW0: 75\n",
            "UW1: 1223\n",
            "UW2: 22\n",
            "V  : 1573\n",
            "W  : 2190\n",
            "Y  : 544\n",
            "Z  : 3307\n",
            "ZH : 47\n",
            "Number of empty phones is: 18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qVfBU-c0FXXO"
      },
      "source": [
        "# соберем статистику на основе среднего значения для каждой фонемы\n",
        "mean_phones_value = {}\n",
        "for phone in phones_dict.keys():\n",
        "    if phones_dict[phone]:\n",
        "        mean_phones_value[phone] = np.mean(phones_dict[phone], axis=0)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zZ4e9U_75jL3"
      },
      "source": [
        "#-----------------------------TODO №2-----------------------------------\n",
        "# построить GMM модель для каждой фонемы (смотри задание2)\n",
        "#-----------------------------------------------------------------------"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P16k6UpnFX77"
      },
      "source": [
        "### Инициализация фонемного графа"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kNO5QhSRFai3"
      },
      "source": [
        "# теперь будем распознавать по словарю, состоящему из конечных слов\n",
        "# для этого нужно загрузить файл лексикона, который определяет из каких фонем состоят наши слова\n",
        "def load_lexicon_dict(lexicon_file):\n",
        "    lexicon_dict = {}\n",
        "    with open(lexicon_file, encoding='utf-8') as fn:\n",
        "        for line in fn:\n",
        "            line = line.strip().split()\n",
        "            lexicon_dict[line[0]] = line[1:]\n",
        "    return lexicon_dict\n",
        "\n",
        "lexicon_file = 'data/lexicon_yes_no.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pxd1c2hQFhD6"
      },
      "source": [
        "Узлы графа теперь представляют собой отдельные фонемы с переходом только в себя и следующий узел (переходов через несколько узлов уже не будет, так как пропуск фонемы в слове нежелателен). Схема такого графа для да/нет (для цифр по аналогии) представлена ниже:\n",
        "\n",
        "![](https://drive.google.com/uc?export=view&id=1IJhR0l0YCPDge05ohigs0_P5gDX66fdM)\n",
        "\n",
        "В качестве <b>model</b> мы будем хранить простой класс <b>AcousticModel</b>, который хранит в себе имя фонемы и ее среднее значение. Также у этого класса есть метод вычисления евклидовой дистанции от хранящегося в нем среднего значения признака фонемы до текущего признака распознаваемой записи, который передается этому методу. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h2YqXJzMFvCl"
      },
      "source": [
        "class AcousticModel:\n",
        "    def __init__(self, phone_name, phone_feats):\n",
        "        self.phone_name = phone_name\n",
        "        self.phone_feats = phone_feats\n",
        "    def distance(self, input_feats):\n",
        "        return float(np.sqrt(sum(pow(self.phone_feats - input_feats, 2))))\n",
        "\n",
        "#-----------------------------TODO №2--------------------------------------------\n",
        "# заменить акустическую модель на основе среднего значения признака на GMM модель\n",
        "class GmmAcousticModel:\n",
        "    def __init__(self, phone_name, phone_feats, covariance_type='full'):\n",
        "        self.phone_name = phone_name\n",
        "        if phone_feats is None:\n",
        "            self.phone_feats = None\n",
        "        else:\n",
        "            n_components = 1 if len(phone_feats) == 1 else 3\n",
        "            self.phone_feats = GaussianMixture(\n",
        "                n_components=n_components,\n",
        "                covariance_type=covariance_type,\n",
        "                random_state=42\n",
        "            ).fit(phone_feats)\n",
        "       \n",
        "    def distance(self, input_feats):\n",
        "        input_feats = np.asarray(input_feats).reshape(1, -1)\n",
        "        return -self.phone_feats.score(input_feats) # -Loglikelihood\n",
        "#--------------------------------------------------------------------------------\n",
        "\n",
        "class State:\n",
        "    def __init__(self, model, index):  \n",
        "        self.model = model                     # вектор признаков узла\n",
        "        self.is_final = False                  # является ли этот узел финальнвм в слове\n",
        "        self.word = None                       # слово эталона (назначается только для финального узла)\n",
        "        self.best_token = None                 # лучший токен (по минимуму дистанции) в узле\n",
        "        self.current_word = None               # текущее слово эталона\n",
        "        self.next_states = []                  # список следующих узлов\n",
        "        self.index = index                     # индекс узла \n",
        "\n",
        "        \n",
        "def load_graph(lexicon_dict, mean_phones_value):\n",
        "    start_state = State(AcousticModel(None, None), 0)\n",
        "    graph = [start_state, ]\n",
        "    state_index = 1\n",
        "    for word in lexicon_dict.keys():\n",
        "        previous_state = start_state\n",
        "        for phone in lexicon_dict[word]:\n",
        "            state = State(AcousticModel(phone, mean_phones_value[phone]), state_index)\n",
        "            state.current_word = word           # слово эталона теперь будет храниться в каждом узле\n",
        "            state.next_states.append(state)     # add loop\n",
        "            previous_state.next_states.append(state)\n",
        "            previous_state = state \n",
        "            graph.append(state)\n",
        "            state_index += 1\n",
        "        if state:\n",
        "            state.word = word\n",
        "            state.is_final = True\n",
        "    return graph\n",
        "\n",
        "def print_graph(graph):\n",
        "    if not os.path.exists('exp'):\n",
        "        os.mkdir('exp')\n",
        "    with open('exp/graph.txt', 'w') as fn:\n",
        "        np.set_printoptions(formatter={'float': '{: 0.1f}'.format})\n",
        "        for state in graph:\n",
        "            next_state_indexes = [s.index for s in state.next_states]\n",
        "            fn.write(\"State: index={} word={} is_final={} next_state_indexes={} phone={} \\n\".format(\n",
        "                state.index, state.word, state.is_final, next_state_indexes, state.model.phone_name))\n",
        "    print(\"*** SEE exp/graph.txt ***\")"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8DOtPoIjFzYp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "77cb2c0b-ac71-40fe-ebee-5f901dc115fd"
      },
      "source": [
        "graph = load_graph(lexicon_dict, mean_phones_value)\n",
        "print_graph(graph)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "*** SEE exp/graph.txt ***\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cC28co6MF1G3"
      },
      "source": [
        "class Token:\n",
        "    def __init__(self, state, dist=0.0, word=\"\"):\n",
        "        self.state = state       # стейт графа, в котором токен находится в текущий момент\n",
        "        self.dist = dist         # общая накопленная дистанция пути, пройденного токеном\n",
        "        self.word = word         # слово, которое распозналось токеном\n",
        "        self.alive = True\n",
        "\n",
        "\n",
        "def beam_pruning(next_tokens, threshold):   \n",
        "    best_token = next_tokens[np.argmin([token.dist for token in next_tokens])]\n",
        "    for token in next_tokens:\n",
        "        if token.dist > best_token.dist + threshold:\n",
        "            token.alive = False\n",
        "    return next_tokens\n",
        "\n",
        "\n",
        "def state_pruning(next_tokens):\n",
        "    for token in next_tokens:  \n",
        "        if not token.state.best_token:\n",
        "            token.state.best_token = token\n",
        "        else:\n",
        "            if token.dist <= token.state.best_token.dist:\n",
        "                token.state.best_token.alive = False\n",
        "                token.state.best_token = token\n",
        "            else:\n",
        "                token.alive = False              \n",
        "    # сбрасываем best_token на None для всеx узлов графа:\n",
        "    for token in next_tokens:                                                   \n",
        "        if token.state.best_token:                     \n",
        "            token.state.best_token = None              \n",
        "    return next_tokens\n",
        "\n",
        "\n",
        "def recognize(filename, features, graph, recognition_results, beam_threshold):\n",
        "\n",
        "    start_state = graph[0]\n",
        "    active_tokens = [Token(start_state), ]\n",
        "    next_tokens = []\n",
        "\n",
        "    #for ftr_frame in tqdm(features, desc=\"recognition...\"):\n",
        "    for ftr_frame in features:\n",
        "        for token in active_tokens:\n",
        "            if token.alive:\n",
        "                for transition_state in token.state.next_states:\n",
        "                    new_token = Token(transition_state, token.dist, token.word)\n",
        "                    new_token.dist += transition_state.model.distance(ftr_frame)\n",
        "                    next_tokens.append(new_token)\n",
        "        # state and beam prunings:\n",
        "        next_tokens = state_pruning(next_tokens)         \n",
        "        next_tokens = beam_pruning(next_tokens, beam_threshold) \n",
        "\n",
        "        active_tokens = next_tokens\n",
        "        next_tokens = []                                    \n",
        "        \n",
        "    # поиск финальных токенов:\n",
        "    final_tokens = []\n",
        "    for token in active_tokens:\n",
        "        if token.state.is_final and token.alive:\n",
        "            final_tokens.append(token)\n",
        "\n",
        "    # если нет финальных, то берем лучший из выживших:\n",
        "    if len(final_tokens) != 0:\n",
        "        win_token = final_tokens[np.argmin([token.dist for token in final_tokens])]\n",
        "    else:\n",
        "        alive_tokens = [token for token in active_tokens if token.alive]\n",
        "        win_token = alive_tokens[np.argmin([token.dist for token in alive_tokens])]\n",
        "        win_token.state.word = win_token.state.current_word\n",
        "\n",
        "    # вывод результата\n",
        "    print(f\"result: {filename:<27} ==> {win_token.state.word}\")\n",
        "\n",
        "    # совпадает ли запись с полученным эталоном:  \n",
        "    record_word = filename.split('_')[0]\n",
        "    etalon_word = win_token.state.word.split('_')[0]\n",
        "    recognition_results.append(etalon_word.lower() == record_word)\n",
        "\n",
        "    return recognition_results"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lK6AYxapF5lo"
      },
      "source": [
        "def run_recognizer(records_data_dict, graph, beam_threshold=10):\n",
        "    start_time = time.time()\n",
        "    recognition_results = []\n",
        "\n",
        "    for filename in records_data_dict.keys():    \n",
        "        recognition_results = recognize(filename, records_data_dict[filename], graph, recognition_results, beam_threshold)\n",
        "\n",
        "    print(\"-\" * 60)\n",
        "    print(f\"WER is: {(1 - sum(recognition_results)/len(recognition_results))*100:.2f}%\")\n",
        "    print(f\"Total time is: {time.time() - start_time:.2f} sec\")\n",
        "    print(\"-\" * 60)"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SVElJh1zF5_E"
      },
      "source": [
        "#def load_data_dict(dir_path):\n",
        "#    data_dict = {}\n",
        "#    for wav_name in os.listdir(dir_path):\n",
        "#        x, sr = librosa.load(os.path.join(dir_path, wav_name), sr=None) \n",
        "#        mfcc = librosa.feature.mfcc(x, sr=sr, n_mfcc=13, \n",
        "#                                    n_fft=int(sr * 0.025),\n",
        "#                                    hop_length=int(sr * 0.01))\n",
        "#        data_dict[wav_name] = mfcc.T\n",
        "#    \n",
        "#    return data_dict"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HDkx9xJbF8BF"
      },
      "source": [
        "### Запустим наше распознавание на базе YES_NO"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m1O-zUzmF-f6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "527c372afe044bddbec2ea1391c32272",
            "9c102618de6743a0ab4ba05c6c85574b",
            "990ea551deb342ac990382af2d04bb77",
            "40eb1dd338cc47498c1e959b1cfb1cf1",
            "76af17706fc64dfd9bab86e40faaaafa",
            "0930b9c8ffc14ee9a1413421676d3b6e",
            "5427f0e21e47485691ca1ab976c0edaa",
            "c5f8ce59f497410a9e552746faf39ea6",
            "2379da6a9ddd49a6888ae7c31c732497",
            "794847c678e44204b9b4d38e2ffe1150",
            "5546021615454b39a11c20cb1f850b29"
          ]
        },
        "outputId": "d5d9a6f8-0ec3-4a03-8c6b-eb2e1fec7843"
      },
      "source": [
        "lexicon_file = 'data/lexicon_yes_no.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph(lexicon_dict, mean_phones_value)\n",
        "records_data_dict = load_data_dict(\"data/yes_no/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=20)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "527c372afe044bddbec2ea1391c32272"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: no_4abb2400_nohash_0        ==> NO\n",
            "result: yes_39a12648_nohash_0       ==> YES\n",
            "result: no_49af4432_nohash_0        ==> NO\n",
            "result: yes_fe1916ba_nohash_0       ==> NO\n",
            "result: no_41474817_nohash_0        ==> NO\n",
            "result: yes_39a6b995_nohash_0       ==> NO\n",
            "result: yes_ff63ab0b_nohash_0       ==> YES\n",
            "result: no_4394fc7c_nohash_0        ==> NO\n",
            "result: yes_fc94edb0_nohash_0       ==> YES\n",
            "result: no_ad89eb1e_nohash_0        ==> NO\n",
            "------------------------------------------------------------\n",
            "WER is: 20.00%\n",
            "Total time is: 0.12 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W-PcgsxRGBbO"
      },
      "source": [
        "### Запустим наше распознавание на базе Digits"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eFlTEI0EGD8L",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466,
          "referenced_widgets": [
            "baa29a42ca12418aa041ca846eb19ba3",
            "9ced10c1a84d4989adaa32cea66c6eee",
            "46bb16ddb2394bbfaa8df86d93ad3991",
            "9ee0a044d0b24ed2b6bd99f9575f6a3d",
            "75057e2204e34b73aee905789f57b8f4",
            "621d1ede50934215b82f24df942c73a8",
            "ebd4f8ee44b042b7b4025097941cd730",
            "035f842c3a6743ffa20f33bf7f1ef70b",
            "ed55779be6d44702a2ff137f8d967c76",
            "6b0ab0de29374d94b6a283e70de52faf",
            "2def0711327746798643315c5e908f4f"
          ]
        },
        "outputId": "cbd6e59c-4483-4903-fa48-f75b6f9e6ddc"
      },
      "source": [
        "lexicon_file = 'data/lexicon_digits.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph(lexicon_dict, mean_phones_value)\n",
        "records_data_dict = load_data_dict(\"data/digits/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=2000)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "baa29a42ca12418aa041ca846eb19ba3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: five_ffd2ba2f_nohash_0      ==> FIVE\n",
            "result: two_fb2f3242_nohash_0       ==> ONE\n",
            "result: five_f852895b_nohash_0      ==> FIVE\n",
            "result: nine_ccea893d_nohash_0      ==> NINE\n",
            "result: four_ffbb695d_nohash_0      ==> FOUR\n",
            "result: seven_fe5c4a7a_nohash_0     ==> FIVE\n",
            "result: three_feb1d305_nohash_0     ==> SIX\n",
            "result: one_fc2411fe_nohash_0       ==> ONE\n",
            "result: seven_fd32732a_nohash_0     ==> SIX\n",
            "result: two_fce65496_nohash_0       ==> SEVEN\n",
            "result: eight_da584bc0_nohash_4     ==> SIX\n",
            "result: three_fce96bac_nohash_0     ==> FIVE\n",
            "result: one_ffa76c4a_nohash_0       ==> ONE\n",
            "result: four_fce65496_nohash_0      ==> ZERO\n",
            "result: six_ffd2ba2f_nohash_0       ==> SIX\n",
            "result: nine_fbe51750_nohash_0      ==> NINE\n",
            "result: eight_daf230ac_nohash_0     ==> SIX\n",
            "result: zero_f92e49f3_nohash_3      ==> SEVEN\n",
            "result: six_ffbb695d_nohash_0       ==> SIX\n",
            "result: zero_f852895b_nohash_0      ==> FIVE\n",
            "------------------------------------------------------------\n",
            "WER is: 55.00%\n",
            "Total time is: 1.69 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G95sGPm4GGRR"
      },
      "source": [
        "### <b>Задание №1</b> (5 баллов):\n",
        "Отрисовать кластеры признаков фонем \"Y EH1 S N OW1\" в двухмерном пространстве. Для понижения размерности можно воспользоваться алгоритмом t-SNE -- https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html. Все пять кластеров должны помещаться на один рисунок и иметь разные цвета. Также укажите на графике какой цвет какой фонеме соответствует.  "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Ответ**:"
      ],
      "metadata": {
        "id": "0jW0HNtG9V3o"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "CNT_FILES = 100\n",
        "CNT_FEATURES = 200\n",
        "PHONEMES = ('Y', 'EH1', 'S', 'N', 'OW1')\n",
        "RANDOM_STATE = 42\n",
        "LR = 300"
      ],
      "metadata": {
        "id": "5ffgAQO3WwfB"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "phones_dict = init_phones_dict(phones_file)\n",
        "train_data_dict = load_data_dict(train_records_dir, count=CNT_FILES)\n",
        "\n",
        "for file_name in train_data_dict.keys():\n",
        "    file_feats = train_data_dict[file_name]\n",
        "    file_ali = ali_dict[file_name]\n",
        "    for frame in range(min(len(file_feats), len(file_ali))):\n",
        "        phones_dict[file_ali[frame]].append(file_feats[frame])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "bb57ad5c54684cc0bb05bea6b16ffd1e",
            "cca416c844a3404490c1694278b8e3d9",
            "f394bb7a383b4b3a8a8c2fb8c330782a",
            "0e1fd36861c049e8ad9c6c4be606dfbb",
            "a6a874cfd99a40b1879aa2c43dd532c1",
            "0c98fd983606429d8bb538ea0f9de6cb",
            "c6af8764d258415592736457c287078f",
            "3e4e237da39a41b185336a389404316a",
            "9ebf68aff9224896bbf99b5090adb5e2",
            "2753694756344cefb8d9416c27ee650d",
            "0cd35107e7404c7994e5cb7747d96e5f"
          ]
        },
        "id": "VVMP6SVdQYUD",
        "outputId": "3a43b5ce-e3a0-4835-b4ac-6a3b83c6ca90"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bb57ad5c54684cc0bb05bea6b16ffd1e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Early stop at 100th file..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "features, labels = [], []\n",
        "\n",
        "for idx, label in enumerate(PHONEMES):\n",
        "    for feature in phones_dict[label][:CNT_FEATURES]:\n",
        "        features.append(feature)\n",
        "        labels.append(idx)"
      ],
      "metadata": {
        "id": "B-PhtyRfQY6K"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "points = TSNE(\n",
        "    n_components=2,\n",
        "    random_state=RANDOM_STATE,\n",
        "    learning_rate=LR,\n",
        "    init='random'\n",
        ").fit_transform(features)"
      ],
      "metadata": {
        "id": "-htZYzXgRkCS"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 12))\n",
        "scatter = plt.scatter(points[:, 0], points[:, 1], c=labels, cmap='gist_rainbow')\n",
        "plt.legend(handles=scatter.legend_elements()[0], labels=PHONEMES)\n",
        "plt.grid()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 700
        },
        "id": "3rKmvaIiQt0w",
        "outputId": "7316e555-12cd-4981-a067-43a5ae32bef7"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Действительно, фонемы делятся на некоторые кластеры, которые слегка пересекаются друг с другом"
      ],
      "metadata": {
        "id": "rHE1owcSWBqt"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LMeiGWg7GIRR"
      },
      "source": [
        "### <b>Задание №2</b> (5 баллов):\n",
        "Заменить модель среднего значения фонемы на GMM. Количестов смесей для каждой фонемы можно выставить в 3. Теперь вместо расстояния мы будем измерять вероятность принадлежности кадра признаков к GMM модели фонемы, находящейся в конкретном узле графа. Чтобы использовать это значение в парадигме нашего алгоритма, в качестве дистанции нужно брать значение -log(x), где x -- предсказанная вероятность. Тогда чем выше вероятность, тем такая импровизированная дистанция будет меньше. Ссылка на питоновскую реализацию GMM -- https://scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html.\n",
        "\n",
        "Что стало с качеством распознавания на двух тестах?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Ответ**:"
      ],
      "metadata": {
        "id": "d-O_qfru96jV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def load_graph_gmm(lexicon_dict, gmm_phones_value, covariance_type='full'):\n",
        "    start_state = State(GmmAcousticModel(None, None, covariance_type), 0)\n",
        "    graph = [start_state,]\n",
        "    state_index = 1\n",
        "    for word in lexicon_dict.keys():\n",
        "        previous_state = start_state\n",
        "        for phone in lexicon_dict[word]:\n",
        "            state = State(GmmAcousticModel(phone, gmm_phones_value[phone], covariance_type), state_index)\n",
        "            state.current_word = word\n",
        "            state.next_states.append(state)\n",
        "            previous_state.next_states.append(state)\n",
        "            previous_state = state \n",
        "            graph.append(state)\n",
        "            state_index += 1\n",
        "        if state:\n",
        "            state.word = word\n",
        "            state.is_final = True\n",
        "    return graph"
      ],
      "metadata": {
        "id": "Is-xDkWCOG14"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "phones_dict = init_phones_dict(phones_file)\n",
        "train_data_dict = load_data_dict(train_records_dir, count=100)\n",
        "\n",
        "for file_name in train_data_dict.keys():\n",
        "    file_feats = train_data_dict[file_name]\n",
        "    file_ali = ali_dict[file_name]\n",
        "    for frame in range(min(len(file_feats), len(file_ali))):\n",
        "        phones_dict[file_ali[frame]].append(file_feats[frame])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "d060bce81dfc403e83361474762f02e4",
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          ]
        },
        "id": "GUcjp14AOHaZ",
        "outputId": "e7119f6f-c04c-4c34-f431-33eb29baf3fa"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d060bce81dfc403e83361474762f02e4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Early stop at 100th file..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Yes/No, GMM с обычной матрицей ковариации"
      ],
      "metadata": {
        "id": "6LNdrguOPixI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lexicon_file = 'data/lexicon_yes_no.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph_gmm(lexicon_dict, phones_dict, covariance_type='full')\n",
        "records_data_dict = load_data_dict(\"data/yes_no/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "ecfe688ae5454107a0898fbc17ebfde0",
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            "d8d8477db0e24349b8aa996050189bb0"
          ]
        },
        "id": "V6betJRNOS-V",
        "outputId": "5c015e06-1f94-4190-ce85-afa81bb62e3b"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ecfe688ae5454107a0898fbc17ebfde0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: no_4abb2400_nohash_0        ==> YES\n",
            "result: yes_39a12648_nohash_0       ==> NO\n",
            "result: no_49af4432_nohash_0        ==> NO\n",
            "result: yes_fe1916ba_nohash_0       ==> YES\n",
            "result: no_41474817_nohash_0        ==> YES\n",
            "result: yes_39a6b995_nohash_0       ==> YES\n",
            "result: yes_ff63ab0b_nohash_0       ==> YES\n",
            "result: no_4394fc7c_nohash_0        ==> NO\n",
            "result: yes_fc94edb0_nohash_0       ==> YES\n",
            "result: no_ad89eb1e_nohash_0        ==> NO\n",
            "------------------------------------------------------------\n",
            "WER is: 30.00%\n",
            "Total time is: 2.36 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Yes/No, GMM с диагональной матрицей ковариации"
      ],
      "metadata": {
        "id": "9d5XvYhUPozo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lexicon_file = 'data/lexicon_yes_no.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph_gmm(lexicon_dict, phones_dict, covariance_type='diag')\n",
        "records_data_dict = load_data_dict(\"data/yes_no/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "de94aac8f6974b18bbbee4bbd0bb52f0",
            "bb23701feea448638cdc16330ffc8cc7",
            "21f9d7072ead4f8b8d2acb3ca37d5d7f",
            "e1774a789058466e90c35a8fd9e8ce89",
            "6fe82559d700434a91ee415c8e1d59c1",
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            "edb4566d478e4b48b3fd76958665fe0b",
            "ed06f8cda7224645ac59c4e3843b309d",
            "7a31a1cc9fe64bc59a23ec091152a49a"
          ]
        },
        "id": "df7F0xRMPQoP",
        "outputId": "6d16ae2e-b203-4fd8-dbde-6f1149dc14fd"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "de94aac8f6974b18bbbee4bbd0bb52f0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: no_4abb2400_nohash_0        ==> NO\n",
            "result: yes_39a12648_nohash_0       ==> YES\n",
            "result: no_49af4432_nohash_0        ==> NO\n",
            "result: yes_fe1916ba_nohash_0       ==> YES\n",
            "result: no_41474817_nohash_0        ==> NO\n",
            "result: yes_39a6b995_nohash_0       ==> NO\n",
            "result: yes_ff63ab0b_nohash_0       ==> YES\n",
            "result: no_4394fc7c_nohash_0        ==> YES\n",
            "result: yes_fc94edb0_nohash_0       ==> YES\n",
            "result: no_ad89eb1e_nohash_0        ==> NO\n",
            "------------------------------------------------------------\n",
            "WER is: 20.00%\n",
            "Total time is: 2.04 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Digits, GMM с обычной матрицей ковариации"
      ],
      "metadata": {
        "id": "l7XsB1YDPrhM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lexicon_file = 'data/lexicon_digits.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph_gmm(lexicon_dict, phones_dict, covariance_type='full')\n",
        "records_data_dict = load_data_dict(\"data/digits/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466,
          "referenced_widgets": [
            "14a07f38de754c82aaae16c65b13bc5d",
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            "a5738b9ed438425f9b6210409301affd",
            "2306f694cd1f4927862adfc0988720d1",
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            "df5045269b6b49c996dfe05956ca589c",
            "09aa9f33f18045f89f355dbe7c6c2712",
            "b8f60fc2ddac49e7b34cdc7c44640487"
          ]
        },
        "id": "zqTokin1PTmm",
        "outputId": "9832dc83-bf3c-4165-82ab-426a666f4552"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "14a07f38de754c82aaae16c65b13bc5d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: five_ffd2ba2f_nohash_0      ==> FIVE\n",
            "result: two_fb2f3242_nohash_0       ==> TWO\n",
            "result: five_f852895b_nohash_0      ==> FIVE\n",
            "result: nine_ccea893d_nohash_0      ==> SEVEN\n",
            "result: four_ffbb695d_nohash_0      ==> FOUR\n",
            "result: seven_fe5c4a7a_nohash_0     ==> SEVEN\n",
            "result: three_feb1d305_nohash_0     ==> SIX\n",
            "result: one_fc2411fe_nohash_0       ==> NINE\n",
            "result: seven_fd32732a_nohash_0     ==> SEVEN\n",
            "result: two_fce65496_nohash_0       ==> SIX\n",
            "result: eight_da584bc0_nohash_4     ==> SIX\n",
            "result: three_fce96bac_nohash_0     ==> SIX\n",
            "result: one_ffa76c4a_nohash_0       ==> ONE\n",
            "result: four_fce65496_nohash_0      ==> FOUR\n",
            "result: six_ffd2ba2f_nohash_0       ==> SIX\n",
            "result: nine_fbe51750_nohash_0      ==> NINE\n",
            "result: eight_daf230ac_nohash_0     ==> SIX\n",
            "result: zero_f92e49f3_nohash_3      ==> SIX\n",
            "result: six_ffbb695d_nohash_0       ==> SIX\n",
            "result: zero_f852895b_nohash_0      ==> FIVE\n",
            "------------------------------------------------------------\n",
            "WER is: 45.00%\n",
            "Total time is: 24.03 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Digits, GMM с диагональной матрицей ковариации"
      ],
      "metadata": {
        "id": "HVlVKVSiPtl7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lexicon_file = 'data/lexicon_digits.txt'\n",
        "lexicon_dict = load_lexicon_dict(lexicon_file)\n",
        "graph = load_graph_gmm(lexicon_dict, phones_dict, covariance_type='diag')\n",
        "records_data_dict = load_data_dict(\"data/digits/records\")\n",
        "\n",
        "run_recognizer(records_data_dict, graph, beam_threshold=100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466,
          "referenced_widgets": [
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            "980f10943cdd41bdbca2428f6d96b9ec",
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            "c007bdf7f637497cbc0977024d215f1c"
          ]
        },
        "id": "xoC7U05POKf9",
        "outputId": "95beb8d4-84b2-4264-e265-4f471a226b3b"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8006a69d7b3949ffbec974bfb996985d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "result: five_ffd2ba2f_nohash_0      ==> FIVE\n",
            "result: two_fb2f3242_nohash_0       ==> SIX\n",
            "result: five_f852895b_nohash_0      ==> FIVE\n",
            "result: nine_ccea893d_nohash_0      ==> NINE\n",
            "result: four_ffbb695d_nohash_0      ==> FOUR\n",
            "result: seven_fe5c4a7a_nohash_0     ==> SEVEN\n",
            "result: three_feb1d305_nohash_0     ==> THREE\n",
            "result: one_fc2411fe_nohash_0       ==> ONE\n",
            "result: seven_fd32732a_nohash_0     ==> SEVEN\n",
            "result: two_fce65496_nohash_0       ==> EIGHT\n",
            "result: eight_da584bc0_nohash_4     ==> EIGHT\n",
            "result: three_fce96bac_nohash_0     ==> THREE\n",
            "result: one_ffa76c4a_nohash_0       ==> ONE\n",
            "result: four_fce65496_nohash_0      ==> FOUR\n",
            "result: six_ffd2ba2f_nohash_0       ==> SIX\n",
            "result: nine_fbe51750_nohash_0      ==> NINE\n",
            "result: eight_daf230ac_nohash_0     ==> EIGHT\n",
            "result: zero_f92e49f3_nohash_3      ==> ZERO\n",
            "result: six_ffbb695d_nohash_0       ==> SIX\n",
            "result: zero_f852895b_nohash_0      ==> ZERO\n",
            "------------------------------------------------------------\n",
            "WER is: 10.00%\n",
            "Total time is: 20.18 sec\n",
            "------------------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "При переходе на GMM с обычной матрицей ковариации качество незначительно выросло, при переходе на GMM с диагональной матрицей ковариации качество выросло значительно. Также GMM с диагональной матрицей ковариации работает быстрее, чем GMM с обычной"
      ],
      "metadata": {
        "id": "8r5eYplwQAFS"
      }
    }
  ]
}