| | |
| | | |
| | | #### API-reference |
| | | ##### Define pipeline |
| | | - `task`: `Tasks.auto_speech_recognition` |
| | | - `task`: `Tasks.voice_activity_detection` |
| | | - `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk |
| | | - `ngpu`: `1` (Defalut), decoding on GPU. If ngpu=0, decoding on CPU |
| | | - `ncpu`: `1` (Defalut), sets the number of threads used for intraop parallelism on CPU |
| | |
| | | - `output_dir`: None (Defalut), the output path of results if set |
| | | |
| | | ### Inference with multi-thread CPUs or multi GPUs |
| | | FunASR also offer recipes [infer.sh](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs_modelscope/asr/TEMPLATE/infer.sh) to decode with multi-thread CPUs, or multi GPUs. |
| | | FunASR also offer recipes [infer.sh](https://github.com/alibaba-damo-academy/FunASR/blob/main/egs_modelscope/vad/TEMPLATE/infer.sh) to decode with multi-thread CPUs, or multi GPUs. |
| | | |
| | | - Setting parameters in `infer.sh` |
| | | - `model`: model name in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope), or model path in local disk |