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{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "vakyansh_tts_demo.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNhhwduU9+eajfOP6r1Y98A",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/harveenchadha/TTS/blob/main/notebooks/vakyansh_tts_demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Installing Dependencies"
      ],
      "metadata": {
        "id": "oyoFPN29HrRt"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "5x4wJQGUaysK",
        "outputId": "90d49030-311e-4100-b42a-3849df217887"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'vakyansh-tts'...\n",
            "remote: Enumerating objects: 466, done.\u001b[K\n",
            "remote: Counting objects: 100% (201/201), done.\u001b[K\n",
            "remote: Compressing objects: 100% (175/175), done.\u001b[K\n",
            "remote: Total 466 (delta 89), reused 64 (delta 22), pack-reused 265\u001b[K\n",
            "Receiving objects: 100% (466/466), 259.27 KiB | 1.39 MiB/s, done.\n",
            "Resolving deltas: 100% (229/229), done.\n",
            "Processing /content/vakyansh-tts/src/glow_tts/monotonic_align\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from monotonic-align==1.1) (1.19.5)\n",
            "Building wheels for collected packages: monotonic-align\n",
            "  Building wheel for monotonic-align (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for monotonic-align: filename=monotonic_align-1.1-cp37-cp37m-linux_x86_64.whl size=237012 sha256=3ffba87629daf17ecf86f538ead38094792d74d16b36cf691371c36f2e2c8ead\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-m1jlgsel/wheels/3a/e4/2d/953a66d439600fcb1836ffba5ef6915b944df396e8228909cb\n",
            "Successfully built monotonic-align\n",
            "Installing collected packages: monotonic-align\n",
            "Successfully installed monotonic-align-1.1\n",
            "running bdist_wheel\n",
            "running build\n",
            "running build_py\n",
            "creating build\n",
            "creating build/lib\n",
            "creating build/lib/tts_infer\n",
            "copying tts_infer/tts.py -> build/lib/tts_infer\n",
            "copying tts_infer/num_to_word_on_sent.py -> build/lib/tts_infer\n",
            "copying tts_infer/transliterate.py -> build/lib/tts_infer\n",
            "copying tts_infer/__init__.py -> build/lib/tts_infer\n",
            "running egg_info\n",
            "creating vakyansh_tts.egg-info\n",
            "writing vakyansh_tts.egg-info/PKG-INFO\n",
            "writing dependency_links to vakyansh_tts.egg-info/dependency_links.txt\n",
            "writing requirements to vakyansh_tts.egg-info/requires.txt\n",
            "writing top-level names to vakyansh_tts.egg-info/top_level.txt\n",
            "writing manifest file 'vakyansh_tts.egg-info/SOURCES.txt'\n",
            "adding license file 'LICENSE.md'\n",
            "writing manifest file 'vakyansh_tts.egg-info/SOURCES.txt'\n",
            "copying tts_infer/requirements.txt -> build/lib/tts_infer\n",
            "installing to build/bdist.linux-x86_64/wheel\n",
            "running install\n",
            "running install_lib\n",
            "creating build/bdist.linux-x86_64\n",
            "creating build/bdist.linux-x86_64/wheel\n",
            "creating build/bdist.linux-x86_64/wheel/tts_infer\n",
            "copying build/lib/tts_infer/tts.py -> build/bdist.linux-x86_64/wheel/tts_infer\n",
            "copying build/lib/tts_infer/num_to_word_on_sent.py -> build/bdist.linux-x86_64/wheel/tts_infer\n",
            "copying build/lib/tts_infer/transliterate.py -> build/bdist.linux-x86_64/wheel/tts_infer\n",
            "copying build/lib/tts_infer/__init__.py -> build/bdist.linux-x86_64/wheel/tts_infer\n",
            "copying build/lib/tts_infer/requirements.txt -> build/bdist.linux-x86_64/wheel/tts_infer\n",
            "running install_egg_info\n",
            "Copying vakyansh_tts.egg-info to build/bdist.linux-x86_64/wheel/vakyansh_tts-0.0.1-py3.7.egg-info\n",
            "running install_scripts\n",
            "adding license file \"LICENSE.md\" (matched pattern \"LICEN[CS]E*\")\n",
            "creating build/bdist.linux-x86_64/wheel/vakyansh_tts-0.0.1.dist-info/WHEEL\n",
            "creating 'dist/vakyansh_tts-0.0.1-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it\n",
            "adding 'tts_infer/__init__.py'\n",
            "adding 'tts_infer/num_to_word_on_sent.py'\n",
            "adding 'tts_infer/requirements.txt'\n",
            "adding 'tts_infer/transliterate.py'\n",
            "adding 'tts_infer/tts.py'\n",
            "adding 'vakyansh_tts-0.0.1.dist-info/LICENSE.md'\n",
            "adding 'vakyansh_tts-0.0.1.dist-info/METADATA'\n",
            "adding 'vakyansh_tts-0.0.1.dist-info/WHEEL'\n",
            "adding 'vakyansh_tts-0.0.1.dist-info/top_level.txt'\n",
            "adding 'vakyansh_tts-0.0.1.dist-info/RECORD'\n",
            "removing build/bdist.linux-x86_64/wheel\n",
            "Obtaining file:///content/vakyansh-tts\n",
            "Requirement already satisfied: Cython==0.29.24 in /usr/local/lib/python3.7/dist-packages (from vakyansh-tts==0.0.1) (0.29.24)\n",
            "Collecting inflect==5.3.0\n",
            "  Downloading inflect-5.3.0-py3-none-any.whl (32 kB)\n",
            "Collecting layers==0.1.5\n",
            "  Downloading layers-0.1.5.tar.gz (5.5 kB)\n",
            "Requirement already satisfied: librosa==0.8.1 in /usr/local/lib/python3.7/dist-packages (from vakyansh-tts==0.0.1) (0.8.1)\n",
            "Collecting matplotlib==3.3.4\n",
            "  Downloading matplotlib-3.3.4-cp37-cp37m-manylinux1_x86_64.whl (11.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 11.5 MB 11.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy==1.19.5 in /usr/local/lib/python3.7/dist-packages (from vakyansh-tts==0.0.1) (1.19.5)\n",
            "Collecting scipy==1.5.4\n",
            "  Downloading scipy-1.5.4-cp37-cp37m-manylinux1_x86_64.whl (25.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 25.9 MB 1.2 MB/s \n",
            "\u001b[?25hCollecting tensorboardX==2.4\n",
            "  Downloading tensorboardX-2.4-py2.py3-none-any.whl (124 kB)\n",
            "\u001b[K     |████████████████████████████████| 124 kB 57.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tensorboard==2.7.0 in /usr/local/lib/python3.7/dist-packages (from vakyansh-tts==0.0.1) (2.7.0)\n",
            "Collecting torch==1.5.1\n",
            "  Downloading torch-1.5.1-cp37-cp37m-manylinux1_x86_64.whl (753.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 753.2 MB 13 kB/s \n",
            "\u001b[?25hCollecting Unidecode==1.3.2\n",
            "  Downloading Unidecode-1.3.2-py3-none-any.whl (235 kB)\n",
            "\u001b[K     |████████████████████████████████| 235 kB 65.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm==4.62.3 in /usr/local/lib/python3.7/dist-packages (from vakyansh-tts==0.0.1) (4.62.3)\n",
            "Collecting fastapi==0.70.0\n",
            "  Downloading fastapi-0.70.0-py3-none-any.whl (51 kB)\n",
            "\u001b[K     |████████████████████████████████| 51 kB 706 kB/s \n",
            "\u001b[?25hCollecting uvicorn==0.15.0\n",
            "  Downloading uvicorn-0.15.0-py3-none-any.whl (54 kB)\n",
            "\u001b[K     |████████████████████████████████| 54 kB 3.2 MB/s \n",
            "\u001b[?25hCollecting gradio==2.5.2\n",
            "  Downloading gradio-2.5.2-py3-none-any.whl (982 kB)\n",
            "\u001b[K     |████████████████████████████████| 982 kB 61.2 MB/s \n",
            "\u001b[?25hCollecting wavio==0.0.4\n",
            "  Downloading wavio-0.0.4-py2.py3-none-any.whl (9.0 kB)\n",
            "Collecting pydload==1.0.9\n",
            "  Downloading pydload-1.0.9-py2.py3-none-any.whl (16 kB)\n",
            "Collecting pydantic!=1.7,!=1.7.1,!=1.7.2,!=1.7.3,!=1.8,!=1.8.1,<2.0.0,>=1.6.2\n",
            "  Downloading pydantic-1.9.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 10.9 MB 35.1 MB/s \n",
            "\u001b[?25hCollecting starlette==0.16.0\n",
            "  Downloading starlette-0.16.0-py3-none-any.whl (61 kB)\n",
            "\u001b[K     |████████████████████████████████| 61 kB 298 kB/s \n",
            "\u001b[?25hCollecting Flask-Login\n",
            "  Downloading Flask_Login-0.5.0-py2.py3-none-any.whl (16 kB)\n",
            "Collecting flask-cachebuster\n",
            "  Downloading Flask-CacheBuster-1.0.0.tar.gz (3.1 kB)\n",
            "Collecting ffmpy\n",
            "  Downloading ffmpy-0.3.0.tar.gz (4.8 kB)\n",
            "Collecting pydub\n",
            "  Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from gradio==2.5.2->vakyansh-tts==0.0.1) (1.1.5)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from gradio==2.5.2->vakyansh-tts==0.0.1) (2.23.0)\n",
            "Requirement already satisfied: Flask>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from gradio==2.5.2->vakyansh-tts==0.0.1) (1.1.4)\n",
            "Collecting Flask-Cors>=3.0.8\n",
            "  Downloading Flask_Cors-3.0.10-py2.py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from gradio==2.5.2->vakyansh-tts==0.0.1) (7.1.2)\n",
            "Collecting markdown2\n",
            "  Downloading markdown2-2.4.2-py2.py3-none-any.whl (34 kB)\n",
            "Collecting analytics-python\n",
            "  Downloading analytics_python-1.4.0-py2.py3-none-any.whl (15 kB)\n",
            "Collecting paramiko\n",
            "  Downloading paramiko-2.9.1-py2.py3-none-any.whl (210 kB)\n",
            "\u001b[K     |████████████████████████████████| 210 kB 61.1 MB/s \n",
            "\u001b[?25hCollecting pycryptodome\n",
            "  Downloading pycryptodome-3.12.0-cp35-abi3-manylinux2010_x86_64.whl (2.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.0 MB 42.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: PyYaml in /usr/local/lib/python3.7/dist-packages (from layers==0.1.5->vakyansh-tts==0.0.1) (3.13)\n",
            "Collecting bashutils\n",
            "  Downloading Bashutils-0.0.4.tar.gz (4.2 kB)\n",
            "Requirement already satisfied: resampy>=0.2.2 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (0.2.2)\n",
            "Requirement already satisfied: pooch>=1.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (1.5.2)\n",
            "Requirement already satisfied: numba>=0.43.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (0.51.2)\n",
            "Requirement already satisfied: audioread>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (2.1.9)\n",
            "Requirement already satisfied: scikit-learn!=0.19.0,>=0.14.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (1.0.1)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (21.3)\n",
            "Requirement already satisfied: soundfile>=0.10.2 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (0.10.3.post1)\n",
            "Requirement already satisfied: joblib>=0.14 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (1.1.0)\n",
            "Requirement already satisfied: decorator>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from librosa==0.8.1->vakyansh-tts==0.0.1) (4.4.2)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.4->vakyansh-tts==0.0.1) (3.0.6)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.4->vakyansh-tts==0.0.1) (2.8.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.4->vakyansh-tts==0.0.1) (0.11.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.4->vakyansh-tts==0.0.1) (1.3.2)\n",
            "Requirement already satisfied: progressbar2 in /usr/local/lib/python3.7/dist-packages (from pydload==1.0.9->vakyansh-tts==0.0.1) (3.38.0)\n",
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            "Installing collected packages: sniffio, scipy, pynacl, monotonic, cryptography, bcrypt, backoff, anyio, starlette, pydub, pydantic, pycryptodome, paramiko, matplotlib, markdown2, h11, Flask-Login, Flask-Cors, flask-cachebuster, ffmpy, bashutils, asgiref, analytics-python, wavio, uvicorn, Unidecode, torch, tensorboardX, pydload, layers, inflect, gradio, fastapi, vakyansh-tts\n",
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            "  Running setup.py develop for vakyansh-tts\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchvision 0.11.1+cu111 requires torch==1.10.0, but you have torch 1.5.1 which is incompatible.\n",
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            "torchaudio 0.10.0+cu111 requires torch==1.10.0, but you have torch 1.5.1 which is incompatible.\n",
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            "Successfully installed Flask-Cors-3.0.10 Flask-Login-0.5.0 Unidecode-1.3.2 analytics-python-1.4.0 anyio-3.4.0 asgiref-3.4.1 backoff-1.10.0 bashutils-0.0.4 bcrypt-3.2.0 cryptography-36.0.1 fastapi-0.70.0 ffmpy-0.3.0 flask-cachebuster-1.0.0 gradio-2.5.2 h11-0.12.0 inflect-5.3.0 layers-0.1.5 markdown2-2.4.2 matplotlib-3.3.4 monotonic-1.6 paramiko-2.9.1 pycryptodome-3.12.0 pydantic-1.9.0 pydload-1.0.9 pydub-0.25.1 pynacl-1.4.0 scipy-1.5.4 sniffio-1.2.0 starlette-0.16.0 tensorboardX-2.4 torch-1.5.1 uvicorn-0.15.0 vakyansh-tts-0.0.1 wavio-0.0.4\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "matplotlib",
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                ]
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-01-04 08:20:03--  https://storage.googleapis.com/vakyaansh-open-models/translit_models/default_lineup.json\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 142.250.141.128, 2607:f8b0:4023:c0b::80\n",
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            "\n",
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            "\n",
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            "  inflating: hi_111_model.pth        \n",
            "  inflating: hi_scripts.json         \n",
            "  inflating: hi_words_a4b.json       \n",
            "--2022-01-04 08:20:05--  https://storage.googleapis.com/vakyansh-open-models/tts/hindi/hi-IN/female_voice_0/glow.zip\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 142.250.141.128, 2607:f8b0:4023:c0b::80\n",
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            "\n",
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            "   creating: glow_ckp/\n",
            "  inflating: glow_ckp/config.json    \n",
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            "--2022-01-04 08:20:12--  https://storage.googleapis.com/vakyansh-open-models/tts/hindi/hi-IN/female_voice_0/hifi.zip\n",
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            "\n",
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            "   creating: hifi_ckp/\n",
            "  inflating: hifi_ckp/config.json    \n",
            "  inflating: hifi_ckp/g_00100000     \n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "!git clone https://github.com/Open-Speech-EkStep/vakyansh-tts\n",
        "os.chdir('vakyansh-tts') \n",
        "!bash install.sh\n",
        "!python setup.py bdist_wheel\n",
        "!pip install -e .\n",
        "os.chdir('tts_infer')\n",
        "!mkdir translit_models\n",
        "os.chdir('translit_models')\n",
        "!wget https://storage.googleapis.com/vakyaansh-open-models/translit_models/default_lineup.json\n",
        "!mkdir hindi\n",
        "os.chdir('hindi')\n",
        "!wget https://storage.googleapis.com/vakyaansh-open-models/translit_models/hindi/hindi_transliteration.zip\n",
        "!unzip hindi_transliteration\n",
        "\n",
        "!wget https://storage.googleapis.com/vakyansh-open-models/tts/hindi/hi-IN/female_voice_0/glow.zip\n",
        "!unzip glow.zip\n",
        "\n",
        "!wget https://storage.googleapis.com/vakyansh-open-models/tts/hindi/hi-IN/female_voice_0/hifi.zip\n",
        "!unzip hifi.zip\n",
        "\n",
        "!rm glow.zip\n",
        "!rm hifi.zip\n",
        "\n",
        "os.chdir('/content/vakyansh-tts/')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Inference Code"
      ],
      "metadata": {
        "id": "NvQoCgYzKbWN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from tts_infer.tts import TextToMel, MelToWav\n",
        "from tts_infer.transliterate import XlitEngine\n",
        "from tts_infer.num_to_word_on_sent import normalize_nums\n",
        "\n",
        "import re\n",
        "from scipy.io.wavfile import write\n",
        "device = 'cpu'\n",
        "\n",
        "text_to_mel = TextToMel(glow_model_dir='/content/vakyansh-tts/tts_infer/translit_models/hindi/glow_ckp', device=device)\n",
        "mel_to_wav = MelToWav(hifi_model_dir='/content/vakyansh-tts/tts_infer/translit_models/hindi/hifi_ckp', device=device)\n",
        "\n",
        "def translit(text, lang):\n",
        "    reg = re.compile(r'[a-zA-Z]')\n",
        "    engine = XlitEngine(lang)\n",
        "    words = [engine.translit_word(word, topk=1)[lang][0] if reg.match(word) else word for word in text.split()]\n",
        "    updated_sent = ' '.join(words)\n",
        "    return updated_sent\n",
        "    \n",
        "def run_tts(text, lang):\n",
        "    text = text.replace('।', '.') # only for hindi models\n",
        "    text_num_to_word = normalize_nums(text, lang) # converting numbers to words in lang\n",
        "    text_num_to_word_and_transliterated = translit(text_num_to_word, lang) # transliterating english words to lang\n",
        "    \n",
        "    mel = text_to_mel.generate_mel(text_num_to_word_and_transliterated)\n",
        "    audio, sr = mel_to_wav.generate_wav(mel)\n",
        "    write(filename='temp.wav', rate=sr, data=audio) # for saving wav file, if needed\n",
        "    return (sr, audio)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TVW_x9L0b5W4",
        "outputId": "28f0a3b9-8f72-4562-db4b-af49699d6cc3"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/vakyansh-tts/tts_infer/translit_models/hindi/glow_ckp/G_250.pth\n",
            "INFO:root:Loaded checkpoint '/content/vakyansh-tts/tts_infer/translit_models/hindi/glow_ckp/G_250.pth' (iteration 250)\n",
            "/content/vakyansh-tts/tts_infer/translit_models/hindi/hifi_ckp/g_00100000\n",
            "Loading '/content/vakyansh-tts/tts_infer/translit_models/hindi/hifi_ckp/g_00100000'\n",
            "Complete.\n",
            "Removing weight norm...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "_, audio = run_tts('hello my name is harveen', 'hi')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aqZ5xOVidczp",
        "outputId": "bdf8f92b-c673-4738-860e-0cbf3f339d6e"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading hi...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Results"
      ],
      "metadata": {
        "id": "jaFjD59HKghg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import IPython.display as ipd\n",
        "ipd.Audio('temp.wav')"
      ],
      "metadata": {
        "id": "zC9I2Zt5fijp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "outputId": "86d09807-41a8-48e7-ec71-4734b6ccbdc8"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/x-wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    }
  ]
}