读取segemet的asr推理

[wwfcnu]

``

inference_pipeline = pipeline(
    task=Tasks.auto_speech_recognition,
    model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')

#segments_result = inference_pipeline_vad(audio_in=waveform)
#print(segments_result["text"])
wav_scp_path = {}
with open("wav.scp")as f1:
     for line in f1:
        wav_id,wav_path = line.strip().split(" ",1)
        wav_scp_path[wav_id] = wav_path



data = []
with open('segments', 'r') as f:
    for line in f:
        line = line.strip().split()
        data.append([line[0],line[1],float(line[2]), float(line[3])])

#print(data)
with open("output.txt","w")as fw:
    for i, segments in enumerate(data):
        
            waveform, sample_rate = soundfile.read(wav_scp_path.get(segments[1]))
            beg_idx = segments[2] * sample_rate
            end_idx = segments[3] * sample_rate
            wav_segment_id = segments[0]
            waveform_slice = waveform[int(beg_idx):int(end_idx)]
            result_segments = inference_pipeline(audio_in=waveform_slice)
            print(result_segments)
            hypothesis = result_segments["text"]
            fw.write(f'{wav_segment_id} {hypothesis}\n')
            fw.flush()

``
想问一下inference_pipeline(audio_in=waveform_slice)支持批次处理吗

[wwfcnu]

输入的语音必须是单通道的吗

[Simon-chai]

哥们，关于支持批次处理的问题，你找到答案了吗？我尝试了自己vad切割音频成数组分段丢给模型预测，效率慢了一个数量级，识别效果也差了