()
| 4 | import time |
| 5 | |
| 6 | def main(): |
| 7 | from funasr import AutoModel |
| 8 | from funasr.utils.postprocess_utils import rich_transcription_postprocess |
| 9 | |
| 10 | print("[SenseVoice] Loading model...") |
| 11 | t0 = time.time() |
| 12 | model = AutoModel( |
| 13 | model="iic/SenseVoiceSmall", |
| 14 | vad_model="fsmn-vad", |
| 15 | vad_kwargs={"max_single_segment_time": 30000}, |
| 16 | device="cpu", |
| 17 | disable_update=True, |
| 18 | ) |
| 19 | print("[SenseVoice] Model loaded in %.1fs" % (time.time()-t0)) |
| 20 | |
| 21 | print("[SenseVoice] Running inference (Chinese)...") |
| 22 | t0 = time.time() |
| 23 | res = model.generate( |
| 24 | input=model.model_path + "/example/zh.mp3", |
| 25 | cache={}, |
| 26 | language="auto", |
| 27 | use_itn=True, |
| 28 | batch_size_s=60, |
| 29 | merge_vad=True, |
| 30 | merge_length_s=15, |
| 31 | ) |
| 32 | print("[SenseVoice] Inference done in %.1fs" % (time.time()-t0)) |
| 33 | |
| 34 | if res and len(res) > 0 and "text" in res[0]: |
| 35 | text = rich_transcription_postprocess(res[0]["text"]) |
| 36 | print("[SenseVoice] Result: %s" % text) |
| 37 | print("[SenseVoice] PASSED") |
| 38 | return 0 |
| 39 | else: |
| 40 | print("[SenseVoice] FAILED - no text in result") |
| 41 | return 1 |
| 42 | |
| 43 | if __name__ == "__main__": |
| 44 | sys.exit(main()) |
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