RTNet | Monaural Speech Enhancement with Recursive Learning | Speech library

by Andong-Li-speech Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | RTNet Summary

RTNet is a Python library typically used in Artificial Intelligence, Speech, Deep Learning applications. RTNet has no bugs, it has no vulnerabilities and it has low support. However RTNet build file is not available. You can download it from GitHub.

Implementation of "Monaural Speech Enhancement with Recursive Learning in the Time Domain".

Support

Quality

Security

License

Reuse

Support

RTNet has a low active ecosystem.

It has 32 star(s) with 6 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 0 have been closed. On average issues are closed in 143 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of RTNet is current.

Quality

RTNet has 0 bugs and 0 code smells.

Security

RTNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

RTNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RTNet 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

RTNet releases are not available. You will need to build from source code and install.

RTNet has no build file. You will be need to create the build yourself to build the component from source.

RTNet saves you 446 person hours of effort in developing the same functionality from scratch.

It has 1055 lines of code, 64 functions and 10 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed RTNet and discovered the below as its top functions. This is intended to give you an instant insight into RTNet implemented functionality, and help decide if they suit your requirements.

Generate mix utterances for train dataset
Generate mix utterances for cv dataset
Generate mix utterances for seen test dataset
Generate the mix utterances for unseen test datasets
Train the model
Run one epoch
Serialize a model into a dictionary
Temporarily set the default TensorType
Calculate the mean squared error
Print a summary of the model
Contexual frame addition
Pad an array with n_hop
Enhances the model
Recreates the training
Compute the OLA gradient
Load a model from a file
Loads a model from a package
Return the data loader
Collate features
Generate features and features

Get all kandi verified functions for this library.

RTNet Key Features

No Key Features are available at this moment for RTNet.

RTNet Examples and Code Snippets

No Code Snippets are available at this moment for RTNet.

Community Discussions

Trending Discussions on RTNet

Commands for reading, loading and unloading drivers on BeagleBone Black?

QUESTION

Commands for reading, loading and unloading drivers on BeagleBone Black?

Asked 2019-Jun-19 at 09:17

I am using a BeagleBone Black with Xenomai and RTnet on top. As some real-time programs are not working it could be that the installed drivers on my BeagleBone Black are still the standard drivers and not the real-time drivers.

As I did not find anything on internet (only how to install drivers for Windows when using BeagleBone Black) I would like to ask you if anybody knows a command for BeagleBone Black to read, load and unload installed drivers on BBB?

...

ANSWER

Answered 2019-Jun-19 at 09:17

I have found the commands for read, load and unload driver/modules. See the following output of the command window: the commands are lsmod for reading, insmod for loading and rmmod for unloading.

Source https://stackoverflow.com/questions/56662284

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install RTNet

You can download it from GitHub.
You can use RTNet 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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