From cced441e5fe032730e8080cc08800e76fd90f029 Mon Sep 17 00:00:00 2001 From: speech_asr <wangjiaming.wjm@alibaba-inc.com> Date: 星期四, 09 二月 2023 15:12:14 +0800 Subject: [PATCH] add file flush --- README.md | 8 ++++++-- 1 files changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index da09f1c..0a43e4a 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ # FunASR: A Fundamental End-to-End Speech Recognition Toolkit -<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锛乕Model Zoo](docs/modelscope_models.md) +<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� ## Release Notes: ### 2023.1.16, funasr-0.1.6 @@ -62,6 +62,9 @@ pip install --editable ./ ``` +## Usage +For users who are new to FunASR and ModelScope, please refer to [FunASR Docs](https://alibaba-damo-academy.github.io/FunASR/index.html). + ## Contact If you have any questions about FunASR, please contact us by @@ -82,7 +85,8 @@ 1. We borrowed a lot of code from [Kaldi](http://kaldi-asr.org/) for data preparation. 2. We borrowed a lot of code from [ESPnet](https://github.com/espnet/espnet). FunASR follows up the training and finetuning pipelines of ESPnet. 3. We referred [Wenet](https://github.com/wenet-e2e/wenet) for building dataloader for large scale data training. -4. We acknowledge [DeepScience](https://github.com/dyyzhmm/FunASR) for contributing the grpc service. +4. We acknowledge [DeepScience](https://www.deepscience.cn) for contributing the grpc service. + ## License This project is licensed under the [The MIT License](https://opensource.org/licenses/MIT). FunASR also contains various third-party components and some code modified from other repos under other open source licenses. -- Gitblit v1.9.1