Home Projects Matcha-TTS
Matcha-TTS
Jupyter Notebook

Matcha-TTS

[ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching

by shivammehta25 · GitHub
Stars
Forks
License
Created
Last commit
deep-learningdiffusion-modeldiffusion-modelsMITJupyter Notebook
View on GitHub
In plain words

Generate natural-sounding speech quickly using a text-to-speech tool on your computer.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
Matcha-TTS — GitHub preview card
📈 Star history
1 3331 332
2026-07-202026-08-31
📈 Track Matcha-TTS

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

[ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching

Matcha-TTS has 1.3k stars on GitHub. It has been forked 210 times. Matcha-TTS is written mainly in Jupyter Notebook. It has been in active development since 2023. Matcha-TTS is available under the MIT license. Its main topics are deep-learning, diffusion-model, diffusion-models, flow-matching.

Frequently asked questions

What is Matcha-TTS?

[ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching

Is Matcha-TTS open source?

Matcha-TTS is an open-source project. It is released under the MIT license.

Is Matcha-TTS free?

Yes. Matcha-TTS is free and open source — you can use, modify and self-host it.

What license does Matcha-TTS use?

Matcha-TTS is available under the MIT license.

What language is Matcha-TTS written in?

Matcha-TTS is written mainly in Jupyter Notebook.

🏅 Maintainer of this project?
olud.ai badge — Matcha-TTS

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=shivammehta25-matcha-tts)](https://olud.ai/project/shivammehta25-matcha-tts.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →
Pyramid-Flow
[ICLR 2025] Pyramidal Flow Matching for Efficient Video Generative Modeling
3.2k · diffusion-models
sharesflow-matchingdiffusion-models
smalldiffusion
Simple and readable code for training and sampling from diffusion models
773 · diffusion
sharesdiffusion-modeldiffusion-models
MeanFlow
PyTorch implementation of MeanFlow & iMF (one-step generative modeling).
1.2k · diffusion-models
sharesflow-matchingdiffusion-models
Irodori-TTS
A Flow Matching-based Text-to-Speech Model with Emoji-driven Style Control
1k · diffusion-models
sharesflow-matchingdiffusion-models
Lumina-T2X
Lumina-T2X is a unified framework for Text to Any Modality Generation
2.2k · aigc
sharesdiffusion-modeldiffusion-models
PnPInversion
[ICLR2024] Official repo for paper "PnP Inversion: Boosting Diffusion-based Editing with 3 Line…
404 · deep-learning
sharesdiffusion-modeldiffusion-models
SynDiff
Official PyTorch implementation of SynDiff described in the paper (https://arxiv.org/abs/2207.0…
330 · deep-learning
sharesdiffusion-modeldiffusion-models
DiffusionFastForward
DiffusionFastForward: a free course and experimental framework for diffusion-based generative m…
682 · diffusion-model
sharesdiffusion-modeldiffusion-models
Helios
Helios: Real Real-Time Long Video Generation Model
2k · acceleration
sharesdiffusion-modeldiffusion-models
1Prompt1Story
🔥ICLR 2025 (Spotlight) One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Usi…
318 · diffusion
sharesdiffusion-modeldiffusion-models

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.