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Releases: nl8590687/ASRT_SpeechRecognition

ASRT v1.3.0 Released

20 May 11:23
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This is a released version of available. version: 1.3.0
一个可以使用的版本,版本号:1.3.0

  1. 增加了对grpc协议的支持

  2. 代码实现上支持了真正的流式识别

  3. Added support for grpc protocol

  4. The code implementation supports real stream recognition


ASRT v1.x is a brand new version, a better ASRT speech recognition service framework.
ASRT v1.x版本是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release uses SpeechModel 251BN, which contains trained model parameter files.
本次发布使用的是SpeechModel251BN,内含训练好的模型参数文件。

ASRT v1.2.0 Released

28 Mar 09:14
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This is a released version of available. version: 1.2.0
一个可以使用的版本,版本号:1.2.0
The version released this time uses the new speech acoustic model SpeechModel251BN, which is faster to train and has a higher recognition rate than the previous SpeechModel251 model! This ASRT release version uses more than 1300 hours of open source data sets for training, and the model recognition effect is more robust and generalization is stronger! The recognition of model parameter files in this version is better than in the previous version, and the correct rate of speech recognition is about 85%. A more performant http-based API was added.
本次发布的版本使用了新的语音声学模型SpeechModel251BN,相比于之前的SpeechModel251模型训练速度更快、识别率更高!本ASRT发布版本使用了1300余小时的开源数据集进行了训练,模型识别效果更鲁棒,泛化性更强!本版本中模型参数文件的识别效果比上一个版本的更佳,语音识别正确率大约85%。一个性能更好的基于http的API接口被加入其中。

ASRT v1.x is a brand new version, a better ASRT speech recognition service framework.
ASRT v1.x版本是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly. To run the speech recognition API server, please use the asrserver.py file. To run the speech recognition demo client based on HTTP protocol, please use the client.py file after using the asrserver.py file. If you need to modify the recognized recording file path, please enter client.py Modified in.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。运行语音识别API服务器请使用asrserver_http.py文件,运行基于HTTP协议的语音识别demo客户端请在使用asrserver_http.py文件后使用client_http.py文件,如果需要修改识别的录音文件路径,请在client_http.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release uses SpeechModel 251BN, which contains trained model parameter files.
本次发布使用的是SpeechModel251BN,内含训练好的模型参数文件。

ASRT v1.1.2 Released

22 Mar 13:15
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This is a released version of available. version: 1.1.2
一个可以使用的版本,版本号:1.1.2
The version released this time uses more open source data sets for training, the model recognition effect is more robust, and the generalization is stronger! There are better performance model parameter files being included than the last. A better performance http-based API interface was added.
本次发布的版本使用了更多的开源数据集进行了训练,模型识别效果更鲁棒,泛化性更强!本版本中模型参数文件的效果比上一个版本的更佳。一个性能更好的基于http的API接口被加入其中。

ASRT v1.x is a brand new version, a better ASRT speech recognition service framework.
ASRT v1.x版本是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly. To run the speech recognition API server, please use the asrserver.py file. To run the speech recognition demo client based on HTTP protocol, please use the client.py file after using the asrserver.py file. If you need to modify the recognized recording file path, please enter client.py Modified in.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。运行语音识别API服务器请使用asrserver_http.py文件,运行基于HTTP协议的语音识别demo客户端请在使用asrserver_http.py文件后使用client_http.py文件,如果需要修改识别的录音文件路径,请在client_http.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v1.1.1 Released

05 Mar 11:48
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This is a released version of available. version: 1.1.1
一个可以使用的版本,版本号:1.1.1
The version released this time uses more open source data sets for training, the model recognition effect is more robust, and the generalization is stronger! There are better performance model parameter files being included than the last. A better performance http-based API interface was added.
本次发布的版本使用了更多的开源数据集进行了训练,模型识别效果更鲁棒,泛化性更强!本版本中模型参数文件的效果比上一个版本的更佳。一个性能更好的基于http的API接口被加入其中。

ASRT v1.x is a brand new version, a better ASRT speech recognition service framework.
ASRT v1.x版本是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly. To run the speech recognition API server, please use the asrserver.py file. To run the speech recognition demo client based on HTTP protocol, please use the client.py file after using the asrserver.py file. If you need to modify the recognized recording file path, please enter client.py Modified in.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。运行语音识别API服务器请使用asrserver.py文件,运行基于HTTP协议的语音识别demo客户端请在使用asrserver.py文件后使用client.py文件,如果需要修改识别的录音文件路径,请在client.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v1.1.0-update1 Released

29 Dec 05:15
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ASRT v1.1.0 Released

04 Dec 18:00
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This is a released version of available.
version: 1.1.0
一个可以使用的版本,版本号:1.1.0
The version released this time uses more open source data sets for training, the model recognition effect is more robust, and the generalization is stronger!
本次发布的版本使用了更多的开源数据集进行了训练,模型识别效果更鲁棒,泛化性更强!

ASRT v1.x is a brand new version, a better ASRT speech recognition service framework.
ASRT v1.x版本是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly. To run the speech recognition API server, please use the asrserver.py file. To run the speech recognition demo client based on HTTP protocol, please use the client.py file after using the asrserver.py file. If you need to modify the recognized recording file path, please enter client.py Modified in.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。运行语音识别API服务器请使用asrserver.py文件,运行基于HTTP协议的语音识别demo客户端请在使用asrserver.py文件后使用client.py文件,如果需要修改识别的录音文件路径,请在client.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v1.0.0 Released

20 Nov 13:22
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This is a released version of available.
version: 1.0.0
一个可以使用的版本,版本号:1.0.0

This release is a brand new version, a better ASRT speech recognition service framework.
本次发布是一个全新的版本,一个更好的ASRT语音识别服务框架。

If you want to build an API server that can perform speech recognition and support the recognition process that runs several times continuously, all the files in this directory are suitable for you to run and use directly. To run the speech recognition API server, please use the asrserver.py file. To run the speech recognition demo client based on HTTP protocol, please use the client.py file after using the asrserver.py file. If you need to modify the recognized recording file path, please enter client.py Modified in.
如果您是想搭建一个能够进行语音识别的API服务端,支持持续运行若干次的识别过程,本目录下的所有文件适合您直接运行和使用。运行语音识别API服务器请使用asrserver.py文件,运行基于HTTP协议的语音识别demo客户端请在使用asrserver.py文件后使用client.py文件,如果需要修改识别的录音文件路径,请在client.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v0.6.1 Released

20 Apr 14:43
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This is a released version of available.
version: 0.6.1
一个可以使用的版本,版本号:0.6.1

This release fixes an issue that may cause file path errors in some cases.
本次发布修复了在部分情况下可能导致文件路径报错的问题。

If you want to run the recognition process of speech recognition one or several times, all the files in this directory are suitable for you to run and use directly. Run the test.py file directly to run the recognition. Run the speech recognition API server, please use asrserver.pyFile, run the voice recognition client based on the HTTP protocol. Use the testClient.py file after using the asrserver.py file. If you need to modify the identified recording file path, please modify it in testClient.py.
如果您是想运行语音识别的一次或若干次的识别过程,本目录下的所有文件适合您直接运行和使用,直接运行一次识别请执行test.py文件,运行语音识别API服务器请使用asrserver.py文件,运行基于HTTP协议的语音识别客户端请在使用asrserver.py文件后使用testClient.py文件,如果需要修改识别的录音文件路径,请在testClient.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v0.6.0 Released

30 Jul 13:47
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This is a released version of available.
version: 0.6.0
一个可以使用的版本,版本号:0.6.0

The error rate of this released model is 25.27% lower than that of v0.5.0. In the test, the error rate dropped to 18.26%.
本次发布的模型的错误率,相比于v0.5.0版本,相对下降了25.27%,在测试中,错误率降至18.26%。

If you want to run the recognition process of speech recognition one or several times, all the files in this directory are suitable for you to run and use directly. Run the test.py file directly to run the recognition. Run the speech recognition API server, please use asrserver.pyFile, run the voice recognition client based on the HTTP protocol. Use the testClient.py file after using the asrserver.py file. If you need to modify the identified recording file path, please modify it in testClient.py.
如果您是想运行语音识别的一次或若干次的识别过程,本目录下的所有文件适合您直接运行和使用,直接运行一次识别请执行test.py文件,运行语音识别API服务器请使用asrserver.py文件,运行基于HTTP协议的语音识别客户端请在使用asrserver.py文件后使用testClient.py文件,如果需要修改识别的录音文件路径,请在testClient.py中修改。

If you want to train your own speech recognition model, the code under GitHub's master branch might be better for you, it gives more options, and dependency files.
如果您想训练自己的语音识别模型,那么GitHub的master分支下的代码可能更适合您,它提供给了更多的选项,以及依赖文件。

This release still uses SpeechModel 251, which contains trained model parameter files.
本次发布仍然使用的是SpeechModel251,内含训练好的模型参数文件。

ASRT v0.5.0 Released

29 Mar 06:42
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This is a released version of available.
version: 0.5.0
一个可以使用的版本,版本号:0.5.0

This version mainly enhances the robustness of the language model and solves the bug of word drop when converting pinyin to text.

这个版本主要是增强了语言模型的鲁棒性,解决了拼音转换到文本时掉字的bug。

This release still uses the SpeechModel 251, and contains the trained model files.

本次发布仍然使用的是SpeechModel251,内含训练好的模型文件。