From b6439f08549df53bcc01eead3a423fa87f09afe4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期六, 15 四月 2023 00:18:10 +0800
Subject: [PATCH] readme
---
README.md | 64 +++++++++++++++++++++----------
1 files changed, 43 insertions(+), 21 deletions(-)
diff --git a/README.md b/README.md
index 3f63c6b..af38341 100644
--- a/README.md
+++ b/README.md
@@ -7,24 +7,17 @@
[**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new)
| [**Highlights**](#highlights)
| [**Installation**](#installation)
-| [**Docs**](https://alibaba-damo-academy.github.io/FunASR/index.html)
+| [**Docs_EN**](https://alibaba-damo-academy.github.io/FunASR/en/index.html)
| [**Tutorial**](https://github.com/alibaba-damo-academy/FunASR/wiki#funasr%E7%94%A8%E6%88%B7%E6%89%8B%E5%86%8C)
| [**Papers**](https://github.com/alibaba-damo-academy/FunASR#citations)
| [**Runtime**](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime)
-| [**Model Zoo**](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)
+| [**Model Zoo**](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/modelscope_models.md)
| [**Contact**](#contact)
+
## What's new:
-### 2023.1.16, funasr-0.1.6
-- 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),
- [Punctuation](https://www.modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary) model and timestamp together. The model could take in several hours long inputs.
-- We release a new type model, [VAD](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 [Model Zoo](docs/modelscope_models.md).
-- We release a new type model, [Punctuation](https://www.modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/summary), which could predict the punctuation of ASR models's results. It could be freely integrated with any ASR models in [Model Zoo](docs/modelscope_models.md).
-- We release a new model, [Data2vec](https://www.modelscope.cn/models/damo/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/summary), an unsupervised pretraining model which could be finetuned on ASR and other downstream tasks.
-- We release a new model, [Paraformer-Tiny](https://www.modelscope.cn/models/damo/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch/summary), a lightweight Paraformer model which supports Mandarin command words recognition.
-- We release a new type model, [SV](https://www.modelscope.cn/models/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/summary), which could extract speaker embeddings and further perform speaker verification on paired utterances. It will be supported for speaker diarization in the future version.
-- We improve the pipeline of modelscope to speedup the inference, by integrating the process of build model into build pipeline.
-- Various new types of audio input types are now supported by modelscope inference pipeline, including wav.scp, wav format, audio bytes, wave samples...
+
+For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases)
## Highlights
- Many types of typical models are supported, e.g., [Tranformer](https://arxiv.org/abs/1706.03762), [Conformer](https://arxiv.org/abs/2005.08100), [Paraformer](https://arxiv.org/abs/2206.08317).
@@ -35,14 +28,37 @@
## Installation
+Install from pip
+```shell
+pip install -U funasr
+# For the users in China, you could install with the command:
+# pip install -U funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple
+```
+
+Or install from source code
+
+
``` sh
git clone https://github.com/alibaba/FunASR.git && cd FunASR
-pip install --editable ./
+pip install -e ./
+# For the users in China, you could install with the command:
+# pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
+
```
+If you want to use the pretrained models in ModelScope, you should install the modelscope:
+
+```shell
+pip install -U modelscope
+# For the users in China, you could install with the command:
+# pip install -U modelscope -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html -i https://mirror.sjtu.edu.cn/pypi/web/simple
+```
+
For more details, please ref to [installation](https://github.com/alibaba-damo-academy/FunASR/wiki)
-## Usage
-For users who are new to FunASR and ModelScope, please refer to [FunASR Docs](https://alibaba-damo-academy.github.io/FunASR/index.html).
+[//]: # ()
+[//]: # (## Usage)
+
+[//]: # (For users who are new to FunASR and ModelScope, please refer to FunASR Docs([CN](https://alibaba-damo-academy.github.io/FunASR/cn/index.html) / [EN](https://alibaba-damo-academy.github.io/FunASR/en/index.html)))
## Contact
@@ -50,14 +66,14 @@
- 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"/> | <div align="left"><img src="docs/images/nwpu.png" width="260"/> | <img src="docs/images/DeepScience.png" width="200"/> </div> |
+|:---------------------------------------------------------------:|:---------------------------------------------------------------:|:-----------------------------------------------------------:|
## Acknowledge
@@ -85,4 +101,10 @@
booktitle={INTERSPEECH},
year={2022}
}
-```
\ No newline at end of file
+@inproceedings{Shi2023AchievingTP,
+ title={Achieving Timestamp Prediction While Recognizing with Non-Autoregressive End-to-End ASR Model},
+ author={Xian Shi and Yanni Chen and Shiliang Zhang and Zhijie Yan},
+ booktitle={arXiv preprint arXiv:2301.12343}
+ year={2023}
+}
+```
--
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