update unittest

speech_asr

2023-03-10 b41e0a1334b8d8e079b74c00f8abc59382d6789e

 README.md

@@ -19,11 +19,11 @@

### 2023.2.17, funasr-0.2.0, modelscope-1.3.0
- We support a new feature, export paraformer models into [onnx and torchscripts](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export) from modelscope. The local finetuned models are also supported.
- We support a new feature, [onnxruntime](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer), you could deploy the runtime without modelscope or funasr, for the [paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model, the rtf of onnxruntime is 3x speedup(0.110->0.038) on cpu, [details](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer#speed).
- We support a new feature, [onnxruntime](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python), you could deploy the runtime without modelscope or funasr, for the [paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) model, the rtf of onnxruntime is 3x speedup(0.110->0.038) on cpu, [details](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime/paraformer/rapid_paraformer#speed).
- We support a new feature, [grpc](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/grpc), you could build the ASR service with grpc, by deploying the modelscope pipeline or onnxruntime.
- We release a new model [paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary), which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords.
- We optimize the timestamp alignment of [Paraformer-large-long](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), the prediction accuracy of timestamp is much improved, and achieving accumulated average shift (aas) of 74.7ms, [details](https://arxiv.org/abs/2301.12343).
- We release a new model, [8k VAD model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary), which could predict the duration of none-silence speech. It could be freely integrated with any ASR models in [modelscope](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary).
- We release a new model, [8k VAD model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary), which could predict the duration of none-silence speech. It could be freely integrated with any ASR models in [modelscope](https://github.com/alibaba-damo-academy/FunASR/discussions/134).
- We release a new model, [MFCCA](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary), a multi-channel multi-speaker model which is independent of the number and geometry of microphones and supports Mandarin meeting transcription.
- We release several new UniASR model: 
[Southern Fujian Dialect model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/summary),
@@ -32,6 +32,8 @@
[Vietnamese model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online/summary), 
[Persian model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/summary).
- We release a new model, [paraformer-data2vec model](https://www.modelscope.cn/models/damo/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/summary), an unsupervised pretraining model on AISHELL-2, which is inited for paraformer model and then finetune on AISHEL-1.
- We release a new feature, the `VAD`, `ASR` and `PUNC` models could be integrated freely, which could be models from [modelscope](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), or the local finetine models. The [demo](https://github.com/alibaba-damo-academy/FunASR/discussions/134).
- We optimized the [punctuation common model](https://www.modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary), enhance the recall and precision, fix the badcases of missing punctuation marks.
- Various new types of audio input types are now supported by modelscope inference pipeline, including: mp3、flac、ogg、opus...
### 2023.1.16, funasr-0.1.6， modelscope-1.2.0
- We release a new version model [Paraformer-large-long](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary), which integrate the [VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) model, [ASR](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary),
@@ -54,6 +56,7 @@
## Installation

``` sh
pip install "modelscope[audio_asr]" --upgrade -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
git clone https://github.com/alibaba/FunASR.git && cd FunASR
pip install --editable ./
```
@@ -68,14 +71,14 @@

- email: [funasr@list.alibaba-inc.com](funasr@list.alibaba-inc.com)

|Dingding group | Wechat group|
|:---:|:---:|
|<div align="left"><img src="docs/images/dingding.jpg" width="250"/> |<img src="docs/images/wechat.png" width="222"/></div>|
|Dingding group |                     Wechat group                      |
|:---:|:-----------------------------------------------------:|
|<div align="left"><img src="docs/images/dingding.jpg" width="250"/> | <img src="docs/images/wechat.png" width="232"/></div> |

## Contributors

| <div align="left"><img src="docs/images/DeepScience.png" width="250"/> |
|:---:|
| <div align="left"><img src="docs/images/damo.png" width="180"/> | <img src="docs/images/DeepScience.png" width="200"/> </div> |
|:---------------------------------------------------------------:|:-----------------------------------------------------------:|

## Acknowledge

@@ -109,4 +112,4 @@
  booktitle={arXiv preprint arXiv:2301.12343}
  year={2023}
}
```
```