| | |
| | | |
| | | from funasr import AutoModel |
| | | |
| | | model = AutoModel(model="/Users/zhifu/Downloads/modelscope_models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch") |
| | | model = AutoModel( |
| | | model="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
| | | vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", |
| | | vad_kwargs={"max_single_segment_time": 60000}, |
| | | punc_model="iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", |
| | | # spk_model="iic/speech_campplus_sv_zh-cn_16k-common", |
| | | ) |
| | | |
| | | res = model(input="/Users/zhifu/Downloads/modelscope_models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav") |
| | | res = model.generate( |
| | | input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", |
| | | cache={}, |
| | | ) |
| | | |
| | | print(res) |
| | | |
| | | |
| | | """ call english model like below for detailed timestamps |
| | | # choose english paraformer model first |
| | | # iic/speech_paraformer_asr-en-16k-vocab4199-pytorch |
| | | res = model.generate( |
| | | input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_en.wav", |
| | | cache={}, |
| | | pred_timestamp=True, |
| | | return_raw_text=True, |
| | | sentence_timestamp=True, |
| | | en_post_proc=True, |
| | | ) |
| | | """ |
| | | |
| | | """ can not use currently |
| | | from funasr import AutoFrontend |
| | | |
| | | frontend = AutoFrontend(model="/Users/zhifu/Downloads/modelscope_models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch") |
| | | frontend = AutoFrontend(model="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch") |
| | | |
| | | fbanks = frontend(input="/Users/zhifu/funasr_github/test_local/wav.scp", batch_size=2) |
| | | fbanks = frontend(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", batch_size=2) |
| | | |
| | | for batch_idx, fbank_dict in enumerate(fbanks): |
| | | res = model(**fbank_dict) |
| | | print(res) |
| | | res = model.generate(**fbank_dict) |
| | | print(res) |
| | | """ |