Breeze ASR 25 for WhisperLiveKit

This repository repackages Breeze ASR 25 into a layout that works directly with WhisperLiveKit custom models and also remains usable with faster-whisper / CTranslate2.

It combines:

This is a compatibility packaging repo. It does not introduce new training or new weights.

Included files

  • breeze-asr-25.pt: Whisper decoder checkpoint for WhisperLiveKit SimulStreaming
  • model.bin: CTranslate2 encoder/decoder weights for faster-whisper
  • config.json, preprocessor_config.json, tokenizer.json, vocabulary.json: faster-whisper runtime files

WhisperLiveKit usage

Point WhisperLiveKit to this Hugging Face repo ID or to a local snapshot of this directory.

Example:

whisperlivekit-server \
  --backend simulstreaming \
  --model-path YOUR_USERNAME/YOUR_REPO_NAME

If you want to set alignment heads explicitly, use WhisperLiveKit's scripts/determine_alignment_heads.py against breeze-asr-25.pt and pass the result with --custom-alignment-heads.

faster-whisper usage

from faster_whisper import WhisperModel

model = WhisperModel("YOUR_USERNAME/YOUR_REPO_NAME", compute_type="float16")
segments, info = model.transcribe("audio.wav")

for segment in segments:
    print(f"[{segment.start:.2f}s -> {segment.end:.2f}s] {segment.text}")

Provenance

Credits

Original Breeze ASR 25 authors

Please credit the Breeze ASR 25 authors and cite their paper:

  • Cheng-Kang Chou
  • Chan-Jan Hsu
  • Ho-Lam Chung
  • Liang-Hsuan Tseng
  • Hsi-Chun Cheng
  • Yu-Kuan Fu
  • Kuan-Po Huang
  • Hung-yi Lee

Paper: A Self-Refining Framework for Enhancing ASR Using TTS-Synthesized Data

Conversion credit

The faster-whisper / CTranslate2 conversion included here is based on SoybeanMilk/faster-whisper-Breeze-ASR-25 by SoybeanMilk.

Usage note

If you redistribute or publish derived packaging of this repo, keep the upstream attribution to both the original Breeze ASR 25 authors and the CTranslate2 conversion author.

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