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LinTO-STT-Kaldi

ASR API based on Kaldi and Vosk. Supports offline and real-time transcription.

See the main README for API docs, Docker options, and serving modes. See ENV.md for all environment variables.

Quick Start

Prerequisites

  • Docker
  • At least 7GB disk space for the image
  • Up to 7GB RAM depending on model

Models

LinTO-STT-Kaldi accepts two kinds of models:

LinTO models (acoustic + language model separately):

  • Download from dl.linto.ai
  • Set MODEL_TYPE=lin
  • Mount volumes: -v <AM_PATH>:/opt/AM -v <LM_PATH>:/opt/LM

Vosk models (all-in-one):

Pull or Build

docker pull lintoai/linto-stt-kaldi

or

docker build -t linto-stt-kaldi:latest --build-arg STT_ENGINE=kaldi .

Run

With LinTO models:

docker run --rm -p 8080:80 \
  -e SERVICE_MODE=http \
  -e MODEL_TYPE=lin \
  -v /path/to/AM:/opt/AM \
  -v /path/to/LM:/opt/LM \
  lintoai/linto-stt-kaldi

With a Vosk model:

docker run --rm -p 8080:80 \
  -e SERVICE_MODE=http \
  -e MODEL_TYPE=vosk \
  -v /path/to/vosk-model:/opt/model \
  lintoai/linto-stt-kaldi

For streaming, use -e SERVICE_MODE=websocket. For Celery task mode, use -e SERVICE_MODE=task with -v /shared/audio:/opt/audio.

For punctuation recovery, add a recasepunc model:

-v /path/to/fr.24000:/opt/PUNCT -e PUNCTUATION_MODEL=/opt/PUNCT

License

AGPLv3 (see LICENSE).

Acknowledgments