kandi X-RAY | semi-supervised-ASR Summary
kandi X-RAY | semi-supervised-ASR Summary
semi-supervised-ASR is a Python library. semi-supervised-ASR has no bugs, it has no vulnerabilities and it has low support. However semi-supervised-ASR build file is not available. You can download it from GitHub.
semi-supervised-ASR
semi-supervised-ASR
Support
Quality
Security
License
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Support
semi-supervised-ASR has a low active ecosystem.
It has 9 star(s) with 2 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 0 have been closed. On average issues are closed in 542 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of semi-supervised-ASR is current.
Quality
semi-supervised-ASR has no bugs reported.
Security
semi-supervised-ASR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
semi-supervised-ASR does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
semi-supervised-ASR releases are not available. You will need to build from source code and install.
semi-supervised-ASR has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed semi-supervised-ASR and discovered the below as its top functions. This is intended to give you an instant insight into semi-supervised-ASR implemented functionality, and help decide if they suit your requirements.
- Initialize weights .
- supervised pretraining
- Perform forward computation .
- Decode the model .
- Return a list of key names .
- Load vocabulary .
- Return a boolean mask for the given sequence length .
- Return a data loader for the given dataset .
- Removes the end of a sequence of sequences .
- Calculate the loss based on the input probabilities .
Get all kandi verified functions for this library.
semi-supervised-ASR Key Features
No Key Features are available at this moment for semi-supervised-ASR.
semi-supervised-ASR Examples and Code Snippets
No Code Snippets are available at this moment for semi-supervised-ASR.
Community Discussions
No Community Discussions are available at this moment for semi-supervised-ASR.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install semi-supervised-ASR
You can download it from GitHub.
You can use semi-supervised-ASR like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use semi-supervised-ASR like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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