From 6013d3c4a9afa81f8f7bdca4e3d9fe84639eb39b Mon Sep 17 00:00:00 2001 From: hnluo <haoneng.lhn@alibaba-inc.com> Date: 星期五, 28 四月 2023 16:38:03 +0800 Subject: [PATCH] Merge pull request #441 from alibaba-damo-academy/dev_lhn --- README.md | 14 ++++++-------- 1 files changed, 6 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 0fb2423..414eb9b 100644 --- a/README.md +++ b/README.md @@ -18,19 +18,17 @@ | [**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) +| [**M2MET2.0 Challenge**](https://github.com/alibaba-damo-academy/FunASR#multi-channel-multi-party-meeting-transcription-20-m2met20-challenge) -## 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: - +### 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)). +### Release notes For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases) ## Highlights - 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) +- We have released large number of academic and industrial pretrained models on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition), ref to [Model Zoo](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_models.html) - 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) - Compared to [Espnet](https://github.com/espnet/espnet) framework, the training speed of large-scale datasets in FunASR is much faster owning to the optimized dataloader. @@ -62,7 +60,7 @@ # 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) +For more details, please ref to [installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html) [//]: # () [//]: # (## Usage) -- Gitblit v1.9.1