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whisper-large-v3-zh to enhance Chinese punctuation mark capabilities. It demonstrates comparable performance to Belle-whisper-large-v3-zh on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST.1from faster_whisper import WhisperModel
2model = WhisperModel("k1nto/Belle-whisper-large-v3-zh-punct-ct2")
3segments, info = model.transcribe("audio.mp3")
4for segment in segments:
5 print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))ct2-transformers-converter --model BELLE-2/Belle-whisper-large-v3-zh-punct --output_dir Belle-whisper-large-v3-zh-punct-ct2 --copy_files tokenizer.json preprocessor_config.json --quantization float16