| egs_modelscope/asr/TEMPLATE/README.md | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| egs_modelscope/asr/TEMPLATE/README_zh.md | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 |
egs_modelscope/asr/TEMPLATE/README.md
@@ -68,6 +68,23 @@ ``` Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/FunASR/discussions/241) #### [Paraformer-contextual Model](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) ```python from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks param_dict = dict() # param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt" param_dict['hotword']="邓郁松 王颖春 王晔君" inference_pipeline = pipeline( task=Tasks.auto_speech_recognition, model="damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404", param_dict=param_dict) rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_hotword.wav') print(rec_result) ``` #### [UniASR Model](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) There are three decoding mode for UniASR model(`fast`、`normal`、`offline`), for more model details, please refer to [docs](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) ```python egs_modelscope/asr/TEMPLATE/README_zh.md
@@ -68,6 +68,23 @@ ``` 演示代码完整版本,请参考[demo](https://github.com/alibaba-damo-academy/FunASR/discussions/241) #### [Paraformer-contextual Model](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) ```python from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks param_dict = dict() # param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt" param_dict['hotword']="邓郁松 王颖春 王晔君" inference_pipeline = pipeline( task=Tasks.auto_speech_recognition, model="damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404", param_dict=param_dict) rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_hotword.wav') print(rec_result) ``` #### [UniASR 模型](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) UniASR 模型有三种解码模式(fast、normal、offline),更多模型细节请参考[文档](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) ```python