From 3d54e6134c3884ada8a22fe8d1b15dc58edbd26f Mon Sep 17 00:00:00 2001
From: jmwang66 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 09 二月 2023 11:25:57 +0800
Subject: [PATCH] fix build_trainer param

---
 README.md |   26 ++++++++++++++++----------
 1 files changed, 16 insertions(+), 10 deletions(-)

diff --git a/README.md b/README.md
index 6bf1278..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
@@ -23,7 +23,7 @@
 - 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.
 
-## Installation(Training and Developing)
+## Installation
 
 - Install Conda:
 ``` sh
@@ -40,16 +40,17 @@
 ```
 For more versions, please see [https://pytorch.org/get-started/locally](https://pytorch.org/get-started/locally)
 
+- Install ModelScope:
 
-If you are in the area of China, you could set the source to speed the downloading.
+If you are in the area of China, you could set the source to speedup the downloading.
 
 ``` sh
 pip config set global.index-url https://mirror.sjtu.edu.cn/pypi/web/simple
 ```
 
-- Install ModelScope:
+Install or upgrade modelscope.
 ``` sh
-pip install "modelscope[audio]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
+pip install "modelscope[audio]" --upgrade -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
 ```
 
 For more details about modelscope, please see [modelscope installation](https://modelscope.cn/docs/%E7%8E%AF%E5%A2%83%E5%AE%89%E8%A3%85)
@@ -61,9 +62,8 @@
 pip install --editable ./
 ```
 
-## Pretrained Model Zoo
-
-We have trained many academic and industrial models, [model hub](docs/modelscope_models.md)
+## 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
 
@@ -71,15 +71,21 @@
 
 - email: [funasr@list.alibaba-inc.com](funasr@list.alibaba-inc.com)
 
-- Dingding group:
-<div align="left"><img src="docs/images/dingding.jpg" width="250"/>!<img src="docs/images/wechat.png" width="222"/></div>
+|Dingding group | Wechat group|
+|:---:|:---:|
+|<div align="left"><img src="docs/images/dingding.jpg" width="250"/> |<img src="docs/images/wechat.png" width="222"/></div>|
 
+## Contributors
+
+| <div align="left"><img src="docs/images/DeepScience.png" width="250"/> |
+|:---:|
 
 ## Acknowledge
 
 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://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