{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m_HkOd4jwqIb"
      },
      "source": [
        "Connect Google drive account"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-RUb7_iJu1mb"
      },
      "outputs": [],
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount(\"/content/drive\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WIvwEf9zydzN"
      },
      "source": [
        "Download and Build Rnnoise and Requirements"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1HigwgxZxEXf"
      },
      "outputs": [],
      "source": [
        "!pip install pyloudnorm\n",
        "!git clone https://github.com/xiph/rnnoise.git\n",
        "!sudo apt-get install curl autoconf automake libtool python-dev pkg-config sox\n",
        "%cd /content/rnnoise\n",
        "!sh autogen.sh\n",
        "!sh configure\n",
        "!make clean\n",
        "!make"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lyz3RjlYuXjz",
        "outputId": "effb28bd-2b59-4ddc-e391-52f534a35e54"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "usage: /content/rnnoise/examples/.libs/rnnoise_demo <noisy speech> <output denoised>\n"
          ]
        }
      ],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vWzQveIIy7QW"
      },
      "source": [
        "Install Coqui TTS"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jyCWXW_2y_nx"
      },
      "outputs": [],
      "source": [
        "!sudo apt-get install espeak-ng\n",
        "!git clone https://github.com/coqui-ai/TTS.git\n",
        "%cd /content/TTS\n",
        "!pip install numpy==1.21.6\n",
        "!pip install black\n",
        "!pip install coverage\n",
        "!pip install isort\n",
        "!pip install nose\n",
        "!pip install pylint==2.10.2\n",
        "!pip install bokeh==1.4.0\n",
        "# core deps\n",
        "#!pip install numpy==1.19.5\n",
        "!pip install cython\n",
        "!pip install scipy>=1.4.0\n",
        "!pip install torch>=1.7\n",
        "!pip install torchaudio\n",
        "!pip install soundfile\n",
        "!pip install librosa==0.8.0\n",
        "!pip install numba==0.53\n",
        "!pip install inflect\n",
        "!pip install tqdm\n",
        "!pip install anyascii\n",
        "!pip install pyyaml\n",
        "!pip install fsspec>=2021.04.0\n",
        "# deps for examples\n",
        "!pip install flask\n",
        "# deps for inference\n",
        "!pip install pysbd\n",
        "# deps for notebooks\n",
        "!pip install umap-learn==0.5.1\n",
        "!pip install pandas\n",
        "# deps for training\n",
        "!pip install matplotlib\n",
        "!pip install tensorboardX\n",
        "!pip install pyworld\n",
        "# coqui stack\n",
        "!pip install trainer\n",
        "!pip install coqpit # config management\n",
        "# chinese g2p deps\n",
        "!pip install jieba\n",
        "!pip install pypinyin\n",
        "# japanese g2p deps\n",
        "!pip install mecab-python3==1.0.3\n",
        "!pip install unidic-lite==1.0.8\n",
        "# gruut+supported langs\n",
        "!pip install gruut[cs,de,es,fr,it,nl,pt,ru,sv]==2.2.3\n",
        "!pip install tf-estimator-nightly==2.8.0.dev2021122109\n",
        "#!pip install bokeh==2.3.0\n",
        "!pip install tensorflow==2.8.0\n",
        "!pip install panel==0.12.1\n",
        "!pip install folium==0.2.1\n",
        "!pip install datascience==0.10.6\n",
        "!pip install imgaug==0.2.6\n",
        "!pip install albumentations==0.1.12\n",
        "!pip install -e .[all,dev,notebooks]  # Select the relevant extras\n",
        "!make system-deps\n",
        "!make install\n",
        "!pip install numpy==1.21.6\n",
        "!pip install TTS\n",
        "!tts --list_models"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EX5ftK4TzPUD"
      },
      "source": [
        "Download VITS model and Generate Sample Wav File"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Vy-BadvazVNM"
      },
      "outputs": [],
      "source": [
        "!tts --text \"I am the very model of a modern Major General\" --model_name \"tts_models/en/ljspeech/vits\" --out_path /content/drive/MyDrive/speech_out/ljspeech-vits.wav"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uSthp75hzZvz"
      },
      "source": [
        "Process Audio Clips"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xyV6G0mozcdk"
      },
      "outputs": [],
      "source": [
        "!python /content/drive/MyDrive/rnnoise.py /content/drive/MyDrive/original"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XS08OyEVzeJA"
      },
      "source": [
        "Fine Tune VITS model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "DviNKw7rzkyK"
      },
      "outputs": [],
      "source": [
        "!CUDA_VISIBLE_DEVICES=\"0\" python /content/drive/MyDrive/train-vits-bg-colab.py --restore_path /root/.local/share/tts/tts_models--en--ljspeech--vits/model_file.pth"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uRa5mrGRlRc9"
      },
      "source": [
        "Generate Speech using Your Fined Tuned Model.  Point the model_path to the checkpoint.pth file and the config_path to the config.json from the trainer output."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BICjNNGulR2M"
      },
      "outputs": [],
      "source": [
        "!tts --text \"I am the very model of a modern Major General\" --config_path \"/content/drive/MyDrive/DIRECTORY/config.json\" --model_path \"/content/drive/MyDrive/DIRECTORY/MODELFILENAME.pth\" --out_path /content/drive/MyDrive/speech_out/words-vits.wav"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IH0v8dCfng9U"
      },
      "source": [
        "Continue Training Run.  \n",
        "Edit the path to reflect the training output from a previous run."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PiM4XGXgnnIc"
      },
      "outputs": [],
      "source": [
        "!CUDA_VISIBLE_DEVICES=\"0\" python /content/drive/MyDrive/train-vits-bg-colab.py --restore_path /content/drive/MyDrive/DATASET-DIRECTORY/traineroutput/TRAINING_RUN/CHECKPOINTFILE.pth --config_path /content/drive/MyDrive/DATASET-DIRECTORY/traineroutput/TRAINING_RUN/config.json"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UZ2WoSCqzqxH"
      },
      "source": [
        "View Memory Usage"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ryma4sViztPk"
      },
      "outputs": [],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-ORJUVXnz4B5"
      },
      "source": [
        "Load Tensorboard"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "J1gPy_jSz551"
      },
      "outputs": [],
      "source": [
        "import torch \n",
        "with torch.no_grad():\n",
        "    torch.cuda.empty_cache()\n",
        "from __future__ import absolute_import, division, print_function, unicode_literals\n",
        "\n",
        "try:\n",
        "  # %tensorflow_version only exists in Colab.\n",
        "  %tensorflow_version 2.x\n",
        "except Exception:\n",
        "  pass\n",
        "  \n",
        "# Load the TensorBoard notebook extension\n",
        "%load_ext tensorboard"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hkt32dP3z9sK"
      },
      "source": [
        "Load Dashboard"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PxPBHCGf0AVt"
      },
      "outputs": [],
      "source": [
        "%tensorboard --logdir /content/drive/MyDrive/bg-dataset/traineroutput/"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [],
      "name": "Voice Clone.ipynb",
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}