| | |
|---|
| | | token = self.converter.ids2tokens(token_int) |
|---|
| | | token = " ".join(token) |
|---|
| | | |
|---|
| | | #if self.tokenizer is not None: |
|---|
| | | # text = self.tokenizer.tokens2text(token) |
|---|
| | | #else: |
|---|
| | | # text = None |
|---|
| | | results.append(token) |
|---|
| | | |
|---|
| | | # assert check_return_type(results) |
|---|
| | |
|---|
| | | input_lens = torch.tensor([stride_size]) |
|---|
| | | asr_result = speech2text(cache, raw_inputs[:, sample_offset: sample_offset + stride_size], input_lens) |
|---|
| | | if len(asr_result) != 0: |
|---|
| | | final_result += asr_result[0] |
|---|
| | | item = {'key': "utt", 'value': [final_result]} |
|---|
| | | final_result += " ".join(asr_result) + " " |
|---|
| | | item = {'key': "utt", 'value': [final_result.strip()]} |
|---|
| | | else: |
|---|
| | | input_lens = torch.tensor([raw_inputs.shape[1]]) |
|---|
| | | cache["encoder"]["is_final"] = is_final |
|---|
| | |
|---|
| | | if __name__ == "__main__": |
|---|
| | | main() |
|---|
| | | |
|---|
| | | # from modelscope.pipelines import pipeline |
|---|
| | | # from modelscope.utils.constant import Tasks |
|---|
| | | # |
|---|
| | | # inference_16k_pipline = pipeline( |
|---|
| | | # task=Tasks.auto_speech_recognition, |
|---|
| | | # model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch') |
|---|
| | | # |
|---|
| | | # rec_result = inference_16k_pipline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav') |
|---|
| | | # print(rec_result) |
|---|
