You can check the [FAQ Page (Chinese)](https://wiki.ailemon.net/docs/asrt-doc/asrt-doc-1deoeud494h4f) first before asking questions to avoid repeating questions.
If there is any abnormality when the program is running, please send a complete screenshot when asking questions, and indicate the CPU architecture, GPU model, operating system, Python, TensorFlow and CUDA versions used, and whether any code has been modified or data sets have been added or deleted, etc. .
This project uses tensorFlow.keras based on deep convolutional neural network and long-short memory neural network, attention mechanism and CTC to implement.
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)
After cloning the repository via git, go to the project root directory; create a subdirectory `/data/speech_data` (you can use a soft link instead) for datasets, and then extract the downloaded datasets directly into it.
Note that in the current version, in the configuration file, six data sets, Thchs30, ST-CMDS, Primewords, aishell-1, aidatatang200, MagicData, are added by default, please delete them if you don’t need them. If you want to use other data sets, you need to add data configuration yourself, and use the standard format supported by ASRT to organize the data in advance.
Before running this project, please install the necessary [Python3 version dependent library](https://github.com/nl8590687/ASRT_SpeechRecognition#python-import)
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 to [download ASRT Client SDK & Demo](https://wiki.ailemon.net/docs/asrt-doc/download).
To test whether it is successful or not that calls api service interface:
If you want to train and use other model(not Model 251bn), make changes in the corresponding position of the `import speech_model_zoo` in the code files.
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.
The released finished software that includes trained model weights can be downloaded from [ASRT download page](https://wiki.ailemon.net/docs/asrt-doc/download).
Github [Releases](https://github.com/nl8590687/ASRT_SpeechRecognition/releases) page includes the archives of the various versions of the software released and it's introduction. Under each version module, there is a zip file that includes trained model weights files.
If you have trouble when install those packages, please run the following script to do it as long as you have a GPU and CUDA 11.2 and cudnn 8.1 have been installed：
## ASRT Client SDK for Calling Speech Recognition API
ASRT provides the abilities to import client SDKs for several platform and programing language for client develop speech recognition features , which work by RPC. Please refer ASRT project documents for detail.
For full content please refer: [Some free Chinese speech datasets (Chinese)](https://blog.ailemon.net/2018/11/21/free-open-source-chinese-speech-datasets/)
* [Teach you how to use ASRT to train Chinese ASR model (Chinese)](<https://blog.ailemon.net/2020/08/20/teach-you-how-use-asrt-train-chinese-asr-model/>)
* [Teach you how to use ASRT to deploy Chinese ASR API Server (Chinese)](<https://blog.ailemon.net/2020/08/27/teach-you-how-use-asrt-deploy-chinese-asr-api-server/>)
For questions about the principles of the statistical language model that are often asked, see:
* [Simple Chinese word frequency statistics to generate N-gram language model (Chinese)](https://blog.ailemon.net/2017/02/20/simple-words-frequency-statistic-without-segmentation-algorithm/)
* [Statistical Language Model: Chinese Pinyin to Words (Chinese)](https://blog.ailemon.net/2017/04/27/statistical-language-model-chinese-pinyin-to-words/)
