docs

游雁

2023-04-22 a1bf1f4d30cbd952264f6b97112735dd41bf253a

docs

 docs/index.rst

@@ -31,12 +31,7 @@
   ./academic_recipe/sd_recipe.md


.. toctree::
   :maxdepth: 1
   :caption: Model Zoo

   ./modelscope_models.md
   ./huggingface_models.md

.. toctree::
   :maxdepth: 1
@@ -56,11 +51,13 @@

   Undo


.. toctree::
   :maxdepth: 1
   :caption: Funasr Library
   :caption: Model Zoo

   ./build_task.md
   ./modelscope_models.md
   ./huggingface_models.md

.. toctree::
   :maxdepth: 1
@@ -82,6 +79,13 @@
   ./benchmark/benchmark_onnx_cpp.md
   ./benchmark/benchmark_libtorch.md


.. toctree::
   :maxdepth: 1
   :caption: Funasr Library

   ./build_task.md

.. toctree::
   :maxdepth: 1
   :caption: Papers

 docs/modelscope_models.md

@@ -13,7 +13,7 @@
|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
|        [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)        | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which ould deal with arbitrary length input wav                                                                                 |
| [paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. |
| [Paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. |
|              [Paraformer](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary)              | CN & EN  | Alibaba Speech Data (50000hours) |    8358    |    68M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
|          [Paraformer-online](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary)           | CN & EN  | Alibaba Speech Data (50000hours) |    8404    |    68M    |     Online     | Which could deal with streaming input                                                                                           |
|       [Paraformer-tiny](https://www.modelscope.cn/models/damo/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch/summary)       |    CN    |  Alibaba Speech Data (200hours)  |    544     |   5.2M    |    Offline     | Lightweight Paraformer model which supports Mandarin command words recognition                                                  |

 egs_modelscope/asr/TEMPLATE/README.md

@@ -1,7 +1,7 @@
# Speech Recognition

> **Note**: 
> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetine. Here we take typic model as example to demonstrate the usage.
> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetine. Here we take the typic models as examples to demonstrate the usage.

## Inference


 egs_modelscope/vad/TEMPLATE/README.md

@@ -1,7 +1,7 @@
# Voice Activity Detection

> **Note**: 
> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetine. Here we take model of FSMN-VAD as example to demonstrate the usage.
> The modelscope pipeline supports all the models in [model zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html#pretrained-models-on-modelscope) to inference and finetine. Here we take the model of FSMN-VAD as example to demonstrate the usage.

## Inference