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ASRT_SpeechRecognition
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README.md
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[![GPL-3.0 Licensed](https://img.shields.io/badge/License-GPL3.0-blue.svg?style=flat)](https://opensource.org/licenses/GPL-3.0)
[![Stars](https://img.shields.io/github/stars/nl8590687/ASRT_SpeechRecognition)](https://github.com/nl8590687/ASRT_SpeechRecognition)
[![TensorFlow Version](https://img.shields.io/badge/Tensorflow-1.15+-blue.svg)](https://www.tensorflow.org/)
[![TensorFlow Version](https://img.shields.io/badge/Tensorflow-2.5+-blue.svg)](https://www.tensorflow.org/)
[![Python Version](https://img.shields.io/badge/Python-3.7+-blue.svg)](https://www.python.org/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5808434.svg)](https://doi.org/10.5281/zenodo.5808434)
@ -40,7 +40,7 @@ ASRT是一个基于深度学习的中文语音识别系统，如果您觉得喜
### 软件
* Linux: Ubuntu 18.04 + / CentOS 7 +
* Python: 3.7 +
* TensorFlow: 1.15, 2.x + (不建议使用最新版和大版本的x.x.0版)
* TensorFlow: 2.5 +
## 快速开始
@ -146,7 +146,7 @@ Github本仓库下[Releases](https://github.com/nl8590687/ASRT_SpeechRecognition
## Python依赖库
* tensorFlow (1.15 - 2.x)
* tensorFlow (2.5+)
* numpy
* wave
* matplotlib

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README_EN.md
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[![GPL-3.0 Licensed](https://img.shields.io/badge/License-GPL3.0-blue.svg?style=flat)](https://opensource.org/licenses/GPL-3.0)
[![Stars](https://img.shields.io/github/stars/nl8590687/ASRT_SpeechRecognition)](https://github.com/nl8590687/ASRT_SpeechRecognition)
[![TensorFlow Version](https://img.shields.io/badge/Tensorflow-1.15+-blue.svg)](https://www.tensorflow.org/)
[![TensorFlow Version](https://img.shields.io/badge/Tensorflow-2.5+-blue.svg)](https://www.tensorflow.org/)
[![Python Version](https://img.shields.io/badge/Python-3.7+-blue.svg)](https://www.python.org/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5808434.svg)](https://doi.org/10.5281/zenodo.5808434)
@ -36,7 +36,7 @@ This project uses tensorFlow.keras based on deep convolutional neural network an
### Software
* Linux: Ubuntu 18.04 + / CentOS 7 +
* Python: 3.7 +
* TensorFlow: 1.15, 2.x + (The latest and x.x.0 are deprecated)
* TensorFlow: 2.5 +
## Quick Start
Take the operation under the Linux system as an example:
@ -144,7 +144,7 @@ At present, the best model can basically reach 85% of Pinyin correct rate on the
## Python Dependency Library
* tensorFlow (1.15 - 2.x)
* tensorFlow (2.5+)
* numpy
* wave
* matplotlib