| | |
| | | # Speech Recognition |
| | | |
| | | > **Note**: |
| | | > The modelscope pipeline supports all the models in [model zoo] to inference and finetine. Here we take model of Paraformer and Paraformer-online as example to demonstrate the usage. |
| | | |
| | | ## Inference |
| | | |
| | | ### Quick start |
| | | #### Paraformer model |
| | | #### [Paraformer model](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) |
| | | ```python |
| | | from modelscope.pipelines import pipeline |
| | | from modelscope.utils.constant import Tasks |
| | |
| | | rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav') |
| | | print(rec_result) |
| | | ``` |
| | | #### [Paraformer-online model](https://www.modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/summary) |
| | | ```python |
| | | inference_pipeline = pipeline( |
| | | task=Tasks.auto_speech_recognition, |
| | | model='damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online', |
| | | ) |
| | | import soundfile |
| | | speech, sample_rate = soundfile.read("example/asr_example.wav") |
| | | |
| | | param_dict = {"cache": dict(), "is_final": False} |
| | | chunk_stride = 7680# 480ms |
| | | # first chunk, 480ms |
| | | speech_chunk = speech[0:chunk_stride] |
| | | rec_result = inference_pipeline(audio_in=speech_chunk, param_dict=param_dict) |
| | | # next chunk, 480ms |
| | | speech_chunk = speech[chunk_stride:chunk_stride+chunk_stride] |
| | | rec_result = inference_pipeline(audio_in=speech_chunk, param_dict=param_dict) |
| | | |
| | | print(rec_result) |
| | | ``` |
| | | Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/FunASR/discussions/241) |
| | | |
| | | #### API-reference |
| | | ##### define pipeline |
| | |
| | | In this case of `wav.scp` input, `output_dir` must be set to save the output results |
| | | - `audio_fs`: audio sampling rate, only set when audio_in is pcm audio |
| | | |
| | | #### Inference with you data |
| | | |
| | | #### Inference with multi-threads on CPU |
| | | ### Inference with you data |
| | | |
| | | #### Inference with multi GPU |
| | | ### Inference with multi-threads on CPU |
| | | |
| | | ### Inference with multi GPU |
| | | |
| | | ## Finetune with pipeline |
| | | |