From e06317e9d0584086af2ea8c11baf822d71674c49 Mon Sep 17 00:00:00 2001 From: zhifu gao <zhifu.gzf@alibaba-inc.com> Date: 星期五, 05 五月 2023 15:50:57 +0800 Subject: [PATCH] Merge pull request #460 from alibaba-damo-academy/dev_zc --- README.md | 6 +++--- 1 files changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 7fd18d4..4128d87 100644 --- a/README.md +++ b/README.md @@ -13,12 +13,12 @@ | [**Highlights**](#highlights) | [**Installation**](#installation) | [**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) +| [**Tutorial_CN**](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**](https://github.com/alibaba-damo-academy/FunASR#multi-channel-multi-party-meeting-transcription-20-m2met20-challenge) +| [**M2MET2.0 Challenge**](https://github.com/alibaba-damo-academy/FunASR#multi-channel-multi-party-meeting-transcription-20-m2met20-challenge) ## What's new: ### Multi-Channel Multi-Party Meeting Transcription 2.0 (M2MET2.0) Challenge @@ -28,7 +28,7 @@ ## 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. -- Gitblit v1.9.1