wehub-resource-sync
64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
#!/usr/bin/env python3
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"""Test Paraformer-Streaming: chunk-by-chunk streaming ASR"""
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import sys
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import time
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import os
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def main():
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import soundfile
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from funasr import AutoModel
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print("[Paraformer-Streaming] Loading model...")
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t0 = time.time()
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model = AutoModel(
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model="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online",
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device="cpu",
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disable_update=True,
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disable_pbar=True,
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)
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print("[Paraformer-Streaming] Model loaded in %.1fs" % (time.time() - t0))
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wav_file = os.path.join(model.model_path, "example/asr_example.wav")
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speech, sample_rate = soundfile.read(wav_file)
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chunk_size = [0, 10, 5]
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encoder_chunk_look_back = 4
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decoder_chunk_look_back = 1
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chunk_stride = chunk_size[1] * 960 # 600ms
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print("[Paraformer-Streaming] Running streaming inference (%.2fs audio, %d chunks)..." % (
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len(speech) / sample_rate, int((len(speech) - 1) / chunk_stride + 1)))
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t0 = time.time()
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cache = {}
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total_chunk_num = int((len(speech) - 1) / chunk_stride + 1)
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all_text = ""
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for i in range(total_chunk_num):
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speech_chunk = speech[i * chunk_stride:(i + 1) * chunk_stride]
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is_final = i == total_chunk_num - 1
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res = model.generate(
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input=speech_chunk,
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cache=cache,
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is_final=is_final,
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chunk_size=chunk_size,
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encoder_chunk_look_back=encoder_chunk_look_back,
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decoder_chunk_look_back=decoder_chunk_look_back,
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)
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txt = res[0].get("text", "") if res else ""
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all_text += txt
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print("[Paraformer-Streaming] Inference done in %.1fs" % (time.time() - t0))
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print("[Paraformer-Streaming] Result: '%s'" % all_text)
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expected = "欢迎大家来体验达摩院推出的语音识别模型"
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if expected in all_text:
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print("[Paraformer-Streaming] PASSED")
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return 0
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else:
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print("[Paraformer-Streaming] FAILED - expected text not found")
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return 1
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if __name__ == "__main__":
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sys.exit(main())
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