update streaming paraformer text process

haoneng.lhn

2023-05-08 1f2a51be9890dc3325c953a927aac41189cd317b

update streaming paraformer text process

 egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/infer.py

@@ -34,6 +34,6 @@
    rec_result = inference_pipeline(audio_in=speech[sample_offset: sample_offset + stride_size],
                                    param_dict=param_dict)
    if len(rec_result) != 0:
        final_result += " ".join(rec_result['text']) + " "
        final_result += rec_result['text'] + " "
        print(rec_result)
print(final_result)

 egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/infer.py

@@ -34,6 +34,6 @@
    rec_result = inference_pipeline(audio_in=speech[sample_offset: sample_offset + stride_size],
                                    param_dict=param_dict)
    if len(rec_result) != 0:
        final_result += " ".join(rec_result['text']) + " "
        final_result += rec_result['text'] + " "
        print(rec_result)
print(final_result.strip())

 funasr/bin/asr_inference_paraformer_streaming.py

@@ -553,12 +553,12 @@
                asr_result = speech2text(cache, raw_inputs[:, sample_offset: sample_offset + stride_size], input_lens)
                if len(asr_result) != 0: 
                    final_result += " ".join(asr_result) + " "
            item = {'key': "utt", 'value': [final_result.strip()]}
            item = {'key': "utt", 'value': final_result.strip()}
        else:
            input_lens = torch.tensor([raw_inputs.shape[1]])
            cache["encoder"]["is_final"] = is_final
            asr_result = speech2text(cache, raw_inputs, input_lens)
            item = {'key': "utt", 'value': asr_result}
            item = {'key': "utt", 'value': " ".join(asr_result)}

        asr_result_list.append(item)
        if is_final: