WWWWxp/M3-TTS
Pytorch Implementation of the paper "M3-TTS: Multi-modal DiT Alignment & Mel-latent for Zero-shot High-fidelity Speech Synthesis"
- Stars
- 124
- Forks
- 3
- Open issues
- 0
- Last push
- 10mo ago
M3-TTS star history
+0 this week
About M3-TTS
M3-TTS is a free, open-source AI voice and audio tool by WWWWxp, written mainly in Python. Pytorch Implementation of the paper "M3-TTS: Multi-modal DiT Alignment & Mel-latent for Zero-shot High-fidelity Speech Synthesis". It has 124 GitHub stars and 3 forks, and was last updated 10mo ago. GitHub doesn't detect a standard license, so check the repository before using it commercially. According to the project, it works on macOS.
- License
- Not detected
- Commercial use
- No license
- Language
- Python
- Stars
- 124
- Last update
- 10mo ago
- Runs on Mac
- Yes (as stated by the project)
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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M3-TTS FAQ
Can I use M3-TTS commercially?
Unclear. No license was detected, which legally means all rights are reserved. Ask the author before using it commercially. This is a plain-English summary, not legal advice.
Is M3-TTS free?
Yes. M3-TTS is open source and free to use. GitHub doesn't detect a standard license, so check the repository before using it commercially.
Does M3-TTS run on a Mac?
Yes. According to the project, M3-TTS works on macOS.
Does M3-TTS need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is M3-TTS still maintained?
It was last updated 10mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to M3-TTS?
Similar free, open-source tools include F5-TTS, Matcha-TTS, index-tts, Irodori-TTS.
Maintain M3-TTS?
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