Home Projects awesome-speech-recognition-speech-synthesis-papers
awesome-speech-recognition-speech-synthesis-papers

awesome-speech-recognition-speech-synthesis-papers

by zzw922cn · GitHub

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

View on GitHub
⭐ Stars
3.1k
🍴 Forks
515
📜 License
MIT
Commercial use OK
📅 Created
2017
🔄 Last commit
2 yr ago
🏷️ Category
acoustic-model
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 →
awesome-speech-recognition-speech-synthesis-papers — GitHub preview card
📈 Star history
3.13k3.12k
2026-07-072026-07-22
📄 About

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

Frequently asked questions

What is awesome-speech-recognition-speech-synthesis-papers?

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

Is awesome-speech-recognition-speech-synthesis-papers open source?

awesome-speech-recognition-speech-synthesis-papers is an open-source project. It is released under the MIT license.

Is awesome-speech-recognition-speech-synthesis-papers free?

Yes. awesome-speech-recognition-speech-synthesis-papers is free and open source — you can use, modify and self-host it.

🏅 Maintainer of this project?
OpenSourceAI badge — awesome-speech-recognition-speech-synthesis-papers

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

[![OpenSourceAI](https://opensourceai.tech/badge.php?tool=zzw922cn-awesome-speech-recognition-speech-synthesis-papers)](https://opensourceai.tech/project/zzw922cn-awesome-speech-recognition-speech-synthesis-papers.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

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