vlomme / Multi Tacotron Voice Cloning
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Phoneme multilingual(Russian-English) voice cloning based on
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Multi-Tacotron Voice Cloning
This repository is a phonemic multilingual (Russian-English) implementation based on Real-Time-Voice-Cloning. it is a four-stage deep learning framework that allows to create a numerical representation of a voice from a few seconds of audio, and to use it to condition a text-to-speech model. If you only need the English version, please use the original implementation.
Этот репозиторий является многоязычной(русско-английской) фонемной реализацией, основанной на Real-Time-Voice-Cloning. Она состоит из четырёх нейронных сетей, которые позволяют создавать числовое представление голоса из нескольких секунд звука и использовать его для создания модели преобразования текста в речь
Example
Quick start
Use the colab online demo
Requirements
You will need the following whether you plan to use the toolbox only or to retrain the models.
≥Python 3.6.
PyTorch (>=1.0.1).
Run pip install -r requirements.txt to install the necessary packages.
A GPU is mandatory, but you don't necessarily need a high tier GPU if you only want to use the toolbox.
Pretrained models
Download the latest here.
Datasets
| Name | Language | Link | Comments | My link | Comments |
|---|---|---|---|---|---|
| Phoneme dictionary | En, Ru | En,Ru | Phoneme dictionary | link | Совместил русский и английский фонемный словарь |
| LibriSpeech | En | link | 300 speakers, 360h clean speech | ||
| VoxCeleb | En | link | 7000 speakers, many hours bad speech | ||
| M-AILABS | Ru | link | 3 speakers, 46h clean speech | ||
| open_tts, open_stt | Ru | open_tts, open_stt | many speakers, many hours bad speech | link | Почистил 4 часа речи одного спикера. Поправил анотацию, разбил на отрезки до 7 секунд |
| Voxforge+audiobook | Ru | link | Many speaker, 25h various quality | link | Выбрал хорошие файлы. Разбил на отрезки. Добавил аудиокниг из интернета. Получилось 200 спикеров по паре минут на каждого |
| RUSLAN | Ru | link | One speaker, 40h good speech | link | Перекодировал в 16кГц |
| Mozilla | Ru | link | 50 speaker, 30h good speech | link | Перекодировал в 16кГц, Раскидал разных пользователей по папкам |
| Russian Single | Ru | link | One speaker, 9h good speech | link | Перекодировал в 16кГц |
Toolbox
You can then try the toolbox:
python demo_toolbox.py -d <datasets_root>
or
python demo_toolbox.py
Wiki
Тренировка (и для других языков)
Training (and for other languages)
Contribution
for any questions, please email me
Papers implemented
| URL | Designation | Title | Implementation source |
|---|---|---|---|
| 1806.04558 | SV2TTS | Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis | CorentinJ |
| 1802.08435 | WaveRNN (vocoder) | Efficient Neural Audio Synthesis | fatchord/WaveRNN |
| 1712.05884 | Tacotron 2 (synthesizer) | Natural TTS Synthesis by Conditioning Wavenet on Mel Spectrogram Predictions | Rayhane-mamah/Tacotron-2 |
| 1710.10467 | GE2E (encoder) | Generalized End-To-End Loss for Speaker Verification | CorentinJ |
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