(Optional) Test Configurationīefore you download any dataset, you can begin by testing your configuration with: If this doesn't work for you, you can manually download them here. Pretrained models are now downloaded automatically.
Install the remaining requirements with pip install -r requirements.txt.Pick the latest stable version, your operating system, your package manager (pip by default) and finally pick any of the proposed CUDA versions if you have a GPU, otherwise pick CPU. This is necessary for reading audio files. I recommend setting up a virtual environment using venv, but this is optional. Python 3.5 or greater should work, but you'll probably have to tweak the dependencies' versions. A GPU is recommended for training and for inference speed, but is not mandatory. You can use your trained encoder models from this repo with it. Go here for more info.Ģ0/08/19: I'm working on resemblyzer, an independent package for the voice encoder (inference only). If you're planning to work on a serious project, my strong advice: find another TTS repo. If this is not your case: proceed with this repository, but you might end up being disappointed by the results.You will get a better voice quality and less prosody errors. If you just want to clone your voice (and not someone else's): I recommend our free plan on Resemble.AI.
Find new instructions in the section below.ġ4/02/21: This repo now runs on PyTorch instead of Tensorflow, thanks to the help of I'm now working full time and I will rarely maintain this repo anymore. Mostly, I've worked on making setup easier. It can also do voice cloning and more, such as cross-language cloning or voice conversion.Ģ8/12/21: I've done a major maintenance update. It's a good and up-to-date TTS repository targeted for the ML community. Generalized End-To-End Loss for Speaker Verificationġ0/01/22: I recommend checking out CoquiTTS. Tacotron: Towards End-to-End Speech Synthesis Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
In the second and third stages, this representation is used as reference to generate speech given arbitrary text. In the first stage, one creates a digital representation of a voice from a few seconds of audio. SV2TTS is a deep learning framework in three stages. Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. This repository is an implementation of Transfer Learning from Speaker Verification to