hangrylabs/melotts repository overview

⁠

⁠Hangry Labs Melo T T S

Easy-to-run text-to-speech Docker images with a browser UI and HTTP API included.

This Hangry Labs fork is built for people who want text to speech to work without a long setup. Install Docker, run one command, open the local UI, or call the API from your own application.

⁠Listen First

Voice examples are available here:

https://hangry-labs.github.io/MeloTTS/examples/⁠

The examples page includes MP3 previews for the main English voices plus Spanish, French, Chinese, Japanese, and Korean.

⁠Project Links

• Voice examples: https://hangry-labs.github.io/MeloTTS/examples/⁠
• GitHub repository: https://github.com/hangry-labs/MeloTTS⁠
• Issues and support: https://github.com/hangry-labs/MeloTTS/issues⁠
• Hangry Labs: https://nuggies.website/⁠

⁠Quick Start

Full multilingual image:

docker run -p 8888:8888 --gpus all hangrylabs/melotts:latest

EN-focused image:

docker run -p 8888:8888 --gpus all hangrylabs/melotts:latest_en

Then open:

http://localhost:8888⁠

The container includes the web UI and the HTTP API on the same port.

⁠What You Get

• Browser UI for manual text-to-speech generation
• HTTP API for applications and automation
• MP3 output from the UI by default
• Backward-compatible WAV API responses unless format is requested
• Sentence-level streaming API for applications that want earlier audio delivery
• Full multilingual image and smaller EN-focused image
• GPU support when Docker/NVIDIA support is available
• Offline-friendly usage once the image and baked model assets are available locally

⁠API Example

Default API behavior returns WAV for backward compatibility:

curl -X POST "http://localhost:8888/tts/generate" ^
  -H "Content-Type: application/json" ^
  -d "{\"text\":\"Hello from Hangry Labs Melo T T S\",\"language\":\"EN\",\"speaker_id\":\"EN-BR\"}" ^
  -o hello.wav

Request MP3 when you want compact output:

curl -X POST "http://localhost:8888/tts/generate" ^
  -H "Content-Type: application/json" ^
  -d "{\"text\":\"Hello from Hangry Labs Melo T T S\",\"language\":\"EN\",\"speaker_id\":\"EN-BR\",\"format\":\"mp3\"}" ^
  -o hello.mp3

Supported formats are listed by:

curl http://localhost:8888/tts/formats

Legacy clients using POST /tts/convert/tts still work. New integrations should use POST /tts/generate.

Streaming API for applications:

curl -X POST "http://localhost:8888/tts/stream" ^
  -H "Content-Type: application/json" ^
  -d "{\"text\":\"First sentence. Second sentence.\",\"language\":\"EN\",\"speaker_id\":\"EN-BR\"}" ^
  -o hello.pcm

Streaming defaults to raw mono pcm_s16le chunks at the model sample rate. You can also request MP3 sentence chunks with "stream_format":"mp3" when MP3 encoding is available. List streaming formats with:

curl http://localhost:8888/tts/stream-formats

⁠Image Tags

• Full multilingual image: latest, <version>
• EN-focused image: latest_en, <version>_en

Example release tags:

docker run -p 8888:8888 --gpus all hangrylabs/melotts:v0.0.8
docker run -p 8888:8888 --gpus all hangrylabs/melotts:v0.0.8_en

⁠Links

• Voice examples: https://hangry-labs.github.io/MeloTTS/examples/⁠
• GitHub: https://github.com/hangry-labs/MeloTTS⁠
• Hangry Labs: https://nuggies.website/⁠
• Issues: https://github.com/hangry-labs/MeloTTS/issues⁠
• Discussions: https://github.com/hangry-labs/MeloTTS/discussions⁠

Docker Hub comments are not monitored regularly. GitHub Issues are the best place to report bugs.

⁠Attribution

This is an independently maintained fork of the original MeloTTS project by Wenliang Zhao, Xumin Yu, and Zengyi Qin:

https://github.com/myshell-ai/MeloTTS⁠

License and attribution are preserved in the repository. Original MeloTTS copyright remains with MyShell.ai; Hangry Labs maintains the Docker packaging, Web UI/API integration, examples page, documentation, release tooling, and other modifications in this fork.