From 4ed8d50d14fe006935dc6289d804d94d752501a7 Mon Sep 17 00:00:00 2001 From: 游雁 <zhifu.gzf@alibaba-inc.com> Date: 星期四, 20 四月 2023 17:49:46 +0800 Subject: [PATCH] docs --- README.md | 15 ++++++++++++--- 1 files changed, 12 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index af38341..29ddd4a 100644 --- a/README.md +++ b/README.md @@ -1,26 +1,35 @@ [//]: # (<div align="left"><img src="docs/images/funasr_logo.jpg" width="400"/></div>) # FunASR: A Fundamental End-to-End Speech Recognition Toolkit +<p align="left"> + <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-brightgreen.svg"></a> + <a href=""><img src="https://img.shields.io/badge/Python->=3.7,<=3.10-aff.svg"></a> + <a href=""><img src="https://img.shields.io/badge/Pytorch-%3E%3D1.11-blue"></a> +</p> <strong>FunASR</strong> hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model released on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun锛� [**News**](https://github.com/alibaba-damo-academy/FunASR#whats-new) | [**Highlights**](#highlights) | [**Installation**](#installation) -| [**Docs_EN**](https://alibaba-damo-academy.github.io/FunASR/en/index.html) +| [**Docs**](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://github.com/alibaba-damo-academy/FunASR/blob/main/docs/modelscope_models.md) | [**Contact**](#contact) +| +[**M2MET2.0 Guidence_CN**](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html) +| [**M2MET2.0 Guidence_EN**](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html) - +## Multi-Channel Multi-Party Meeting Transcription 2.0 (M2MET2.0) Challenge +We are pleased to announce that the M2MeT2.0 challenge will be held in the near future. The baseline system is conducted on FunASR and is provided as a receipe of AliMeeting corpus. For more details you can see the guidence of M2MET2.0 ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)). ## What's new: 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). +- FunASR supports speech recognition(ASR), Multi-talker ASR, Voice Activity Detection(VAD), Punctuation Restoration, Language Models, Speaker Verification and Speaker diarization. - We have released large number of academic and industrial pretrained models on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition) - The pretrained model [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) obtains the best performance on many tasks in [SpeechIO leaderboard](https://github.com/SpeechColab/Leaderboard) - FunASR supplies a easy-to-use pipeline to finetune pretrained models from [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition) -- Gitblit v1.9.1