From cf8e000a84e888495dcf30c4dbfecea1ee7ab4e2 Mon Sep 17 00:00:00 2001 From: jmwang66 <wangjiaming.wjm@alibaba-inc.com> Date: 星期一, 07 八月 2023 16:13:37 +0800 Subject: [PATCH] Merge pull request #807 from alibaba-damo-academy/dev_wjm --- README.md | 6 ++++-- 1 files changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 835fa96..24e62e7 100644 --- a/README.md +++ b/README.md @@ -28,9 +28,9 @@ <a name="whats-new"></a> ## What's new: - +- 2023/08/07: The real-time transcription service (CPU) of Mandarin has been released. For more details, please refer to ([Deployment documentation](funasr/runtime/docs/SDK_tutorial_online.md)). - 2023/07/17: BAT is released, which is a low-latency and low-memory-consumption RNN-T model. For more details, please refer to ([BAT](egs/aishell/bat)). -- 2023/07/03: The CPU version of the Chinese offline file transcription service has been released. For more details, please refer to ([Deployment documentation](funasr/runtime/docs/SDK_tutorial.md)). +- 2023/07/03: The offline file transcription service (CPU) of Mandarin has been released. For more details, please refer to ([Deployment documentation](funasr/runtime/docs/SDK_tutorial.md)). - 2023/06/26: ASRU2023 Multi-Channel Multi-Party Meeting Transcription Challenge 2.0 completed the competition and announced the results. For more details, please refer to ([M2MeT2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)). @@ -46,6 +46,8 @@ <a name="quick-start"></a> ## Quick Start +Quick start for new users锛圼tutorial](https://alibaba-damo-academy.github.io/FunASR/en/funasr/quick_start_zh.html)锛� + FunASR supports inference and fine-tuning of models trained on industrial datasets of tens of thousands of hours. For more details, please refer to ([modelscope_egs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)). It also supports training and fine-tuning of models on academic standard datasets. For more details, please refer to([egs](https://alibaba-damo-academy.github.io/FunASR/en/academic_recipe/asr_recipe.html)). The models include speech recognition (ASR), speech activity detection (VAD), punctuation recovery, language model, speaker verification, speaker separation, and multi-party conversation speech recognition. For a detailed list of models, please refer to the [Model Zoo](https://github.com/alibaba-damo-academy/FunASR/blob/main/docs/model_zoo/modelscope_models.md): -- Gitblit v1.9.1