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Phoneme multilingual(Russian-English) voice cloning based on

Home Page: https://github.com/CorentinJ/Real-Time-Voice-Cloning

License: Other

Jupyter Notebook 0.98% Python 99.02%

multi-tacotron-voice-cloning's Introduction

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

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

Pretrained models

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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