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https://github.com/modelscope/FunASR
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Merge branch 'main' of github.com:alibaba-damo-academy/FunASR
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@ -144,7 +144,7 @@ for i in range(total_chunk_num):
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```
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```
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Note: `chunk_size` is the configuration for streaming latency.` [0,10,5]` indicates that the real-time display granularity is `10*60=600ms`, and the lookahead information is `5*60=300ms`. Each inference input is `600ms` (sample points are `16000*0.6=960`), and the output is the corresponding text. For the last speech segment input, `is_final=True` needs to be set to force the output of the last word.
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Note: `chunk_size` is the configuration for streaming latency.` [0,10,5]` indicates that the real-time display granularity is `10*60=600ms`, and the lookahead information is `5*60=300ms`. Each inference input is `600ms` (sample points are `16000*0.6=960`), and the output is the corresponding text. For the last speech segment input, `is_final=True` needs to be set to force the output of the last word.
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### Voice Activity Detection (streaming)
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### Voice Activity Detection (Non-Streaming)
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```python
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```python
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from funasr import AutoModel
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from funasr import AutoModel
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@ -153,7 +153,7 @@ wav_file = f"{model.model_path}/example/asr_example.wav"
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res = model.generate(input=wav_file)
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res = model.generate(input=wav_file)
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print(res)
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print(res)
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```
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```
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### Voice Activity Detection (Non-streaming)
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### Voice Activity Detection (Streaming)
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```python
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```python
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from funasr import AutoModel
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from funasr import AutoModel
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@ -17,6 +17,6 @@ model = AutoModel(model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-com
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res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
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res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
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hotword='达摩院 魔搭',
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hotword='达摩院 魔搭',
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# sentence_timestamp=True,
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# sentence_timestamp=True, # return sentence level information when spk_model is not given
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)
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)
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print(res)
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print(res)
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@ -212,7 +212,7 @@ def distribute_spk(sentence_list, sd_time_list):
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if overlap > max_overlap:
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if overlap > max_overlap:
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max_overlap = overlap
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max_overlap = overlap
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sentence_spk = spk
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sentence_spk = spk
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d['spk'] = sentence_spk
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d['spk'] = int(sentence_spk)
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sd_sentence_list.append(d)
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sd_sentence_list.append(d)
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return sd_sentence_list
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return sd_sentence_list
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