Giter Site home page Giter Site logo

zhenye234 / comospeech Goto Github PK

View Code? Open in Web Editor NEW
170.0 11.0 17.0 2.42 MB

CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency Model

License: MIT License

Python 98.70% Cython 1.30%
consistency-models diffusion-models speech text-to-speech tts speech-synthesis

comospeech's People

Contributors

eschmidbauer avatar grace9994 avatar zhenye234 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

comospeech's Issues

singing voice synthesis

The paper mentions using CoMoSpeech for the SVS task and briefly describes feature extraction, but I can't find that feature extraction or summing with the phoneme features in the code. Is that planned for release in the future?

Thanks!

作者你好,请问论文中的Eq.(7)是如何推导的?有点没读懂

作者你好,读论文看Eq.(7)还是没懂是如何推导出来的,drift coefficient为f(t)=t,diffusion coefficient为g(t)=1,那么\sigma(t)=t,然后再结合Eq.(4),请问是带入到Eq.(3)这个ODE吗?我自己推了下还是没得到Eq.(7)。不知道是我哪里理解有误?谢谢!

pretrained models available

Hello, thank you for sharing this project. I was hoping to test it out for inference and fine-tuning but could not see any pretrained models available to do so, would it be possible to share an english model?

Generate audio with distinct electric sound, when train on Mandarin custom datasets

Hi, I replace zh pinyin phonemes and finish the network for multi speakers (without feed spk_emb to GradLogPEstimator2d), when I train teacher model on custom datasets with 17 speakers (each speakers 6000 wavs) about 108 epochs, the teacher model generate audio still contain distinct electric sound, is that normal?
Moreover, I change network to feed spk_emb to GradLogPEstimator2d and find the network can quickly reconstruct the timbre of different speakers (only about 2 epoch), but still contain distinct electric sound, how can I work out for it? or just wait more epochs?
Looking forward for your kind reply

你好,请问歌声合成的教师模型使用什么模型?

因为本文的教师模型为grad-TTS,该模型仅针对语音合成,所以想问一下如果想要复现SVS部分:
1.需要用什么模型作为教师模型?参数如何设置?
2.已经获得opencpop数据集,需要做哪些预处理?修改哪些训练参数?
3.声码器可以使用como-SVC的声码器(m4singer-hifigan)吗?如果不行,需要修改哪些参数?
非常感谢您的解答:)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.