ASRT_SpeechRecognition/README_EN.md

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# A Deep-Learning-Based Chinese Speech Recognition System
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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) [![TensorFlow Version](https://img.shields.io/badge/Tensorflow-1.4+-blue.svg)](https://www.tensorflow.org/) [![Keras Version](https://img.shields.io/badge/Keras-2.0+-blue.svg)](https://keras.io/) [![Python Version](https://img.shields.io/badge/Python-3.x-blue.svg)](https://www.python.org/)
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**ReadMe Language** | [中文版](https://github.com/nl8590687/ASRT_SpeechRecognition/blob/master/README.md) | English |
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[**View this project's wiki document (Chinese)**](https://github.com/nl8590687/ASRT_SpeechRecognition/wiki)
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If you have any questions in your works with this project, welcome to put up issues in this repo and I will response as soon as possible.
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You can check the [FAQ Page (Chinese)](https://github.com/nl8590687/ASRT_SpeechRecognition/wiki/issues) first before asking questions to avoid repeating questions.
A post about ASRT's introduction
* [ASRT: Chinese Speech Recognition System (Chinese)](https://blog.ailemon.me/2018/08/29/asrt-a-chinese-speech-recognition-system/)
For questions about the principles of the statistical language model that are often asked, see:
* [Simple word frequency statistics without Chinese word segmentation algorithm (Chinese)](https://blog.ailemon.me/2017/02/20/simple-words-frequency-statistic-without-segmentation-algorithm/)
* [Statistical Language Model: Chinese Pinyin to Words (Chinese)](https://blog.ailemon.me/2017/04/27/statistical-language-model-chinese-pinyin-to-words/)
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## Introduction
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This project uses Keras, TensorFlow based on deep convolutional neural network and long-short memory neural network, attention mechanism and CTC to implement.
* **Steps**
First, clone the project to your computer through Git, and then download the data sets needed for the training of this project. For the download links, please refer to [End of Document](https://github.com/nl8590687/ASRT_SpeechRecognition/blob/master/README_EN.md#data-sets)
```shell
$ git clone https://github.com/nl8590687/ASRT_SpeechRecognition.git
```
Or you can use the "Fork" button to copy a copy of the project and then clone it locally with your own SSH key.
After cloning the repository via git, go to the project root directory; create a subdirectory `dataset/` (you can use a soft link instead), and then extract the downloaded datasets directly into it.
```shell
$ cd ASRT_SpeechRecognition
$ mkdir dataset
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$ tar zxf <dataset zip files name> -C dataset/
```
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Then, you need to copy all the files in the 'datalist' directory to the dataset directory, that is, put them together with the data set.
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```shell
$ cp -rf datalist/* dataset/
```
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Currently available models are 24, 25 and 251
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Before running this project, please install the necessary [Python3 version dependent library](https://github.com/nl8590687/ASRT_SpeechRecognition#python-import)
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To start training this project, please execute:
```shell
$ python3 train_mspeech.py
```
To start the test of this project, please execute:
```shell
$ python3 test_mspeech.py
```
Before testing, make sure the model file path filled in the code files exists.
ASRT API Server startup please execute:
```shell
$ python3 asrserver.py
```
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Please note that after opening the API server, you need to use the client software corresponding to this ASRT project for voice recognition. For details, see the Wiki documentation [ASRT Client Demo](https://github.com/nl8590687/ASRT_SpeechRecognition/wiki/ClientDemo).
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If you want to train and use Model 251, make changes in the corresponding position of the `import SpeechModel` in the code files.
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If there is any problem during the execution of the program or during use, it can be promptly put forward in the issue, and I will reply as soon as possible.
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## Model
### Speech Model
CNN + LSTM/GRU + CTC
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The maximum length of the input audio is 16 seconds, and the output is the corresponding Chinese pinyin sequence.
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* Questions about downloading trained models
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The complete source program that includes trained model weights can be obtained from the archives of the various versions of the software released in the [releases](https://github.com/nl8590687/ASRT_SpeechRecognition/releases) page of Github.
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### Language Model
Maximum Entropy Hidden Markov Model Based on Probability Graph.
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The input is a Chinese pinyin sequence, and the output is the corresponding Chinese character text.
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## About Accuracy
At present, the best model can basically reach 80% of Pinyin correct rate on the test set.
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However, as the current international and domestic teams can achieve 98%, the accuracy rate still needs to be further improved.
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## Python libraries that need importing
* python_speech_features
* TensorFlow
* Keras
* Numpy
* wave
* matplotlib
* math
* Scipy
* h5py
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* http
* urllib
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## Data Sets
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* **Tsinghua University THCHS30 Chinese voice data set**
data_thchs30.tgz
[Download](<http://www.openslr.org/resources/18/data_thchs30.tgz>)
test-noise.tgz
[Download](<http://www.openslr.org/resources/18/test-noise.tgz>)
resource.tgz
[Download](<http://www.openslr.org/resources/18/resource.tgz>)
* **Free ST Chinese Mandarin Corpus**
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ST-CMDS-20170001_1-OS.tar.gz
[Download](<http://www.openslr.org/resources/38/ST-CMDS-20170001_1-OS.tar.gz>)
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* **AIShell-1 Open Source Dataset**
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data_aishell.tgz
[Download](<http://www.openslr.org/resources/33/data_aishell.tgz>)
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Noteunzip this dataset
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```
$ tar xzf data_aishell.tgz
$ cd data_aishell/wav
$ for tar in *.tar.gz; do tar xvf $tar; done
```
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* **Primewords Chinese Corpus Set 1**
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primewords_md_2018_set1.tar.gz
[Download](<http://www.openslr.org/resources/47/primewords_md_2018_set1.tar.gz>)
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Special thanks! Thanks to the predecessors' public voice data set.
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If the provided dataset link cannot be opened and downloaded, click this link [OpenSLR](http://www.openslr.org)
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## Logs
Links: [Progress Logs](https://github.com/nl8590687/ASRT_SpeechRecognition/blob/master/log.md)
## Contributors
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[@zw76859420](https://github.com/zw76859420)
@madeirak @ZJUGuoShuai @williamchenwl
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@nl8590687 (repo owner)
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[**Donate**](https://github.com/nl8590687/ASRT_SpeechRecognition/wiki/donate)