VAD-python | Voice Activity Detector in Python | Machine Learning library

by marsbroshok Python Version: Current License: No License

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

kandi X-RAY | VAD-python Summary

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

Voice Activity Detector in Python

Support

Quality

Security

License

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Support

VAD-python has a low active ecosystem.

It has 434 star(s) with 130 fork(s). There are 20 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 7 have been closed. On average issues are closed in 7 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of VAD-python is current.

Quality

VAD-python has 0 bugs and 0 code smells.

Security

VAD-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

VAD-python code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

VAD-python 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

VAD-python releases are not available. You will need to build from source code and install.

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

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Detects speech of the audio
Median filter
Calculates the normalized energy of the data
Establish a dictionary of energy frequencies
Sum the energy in the given frequency range
Smooth the speech detection
Calculates the energy of the data
Calculate the amplitudes
Calculate the frequencies of the audio data
Plot the detected speech regions
Detect speech
Convert a list of windows to readible labels
Save data to file

Get all kandi verified functions for this library.

VAD-python Key Features

No Key Features are available at this moment for VAD-python.

VAD-python Examples and Code Snippets

No Code Snippets are available at this moment for VAD-python.

Community Discussions

Trending Discussions on VAD-python

webRTC: getting VAD data on WAV audio in python

QUESTION

webRTC: getting VAD data on WAV audio in python

Asked 2022-Jan-31 at 11:45

I am trying to run the example code of webRTC VAD found here.

But when I feed it a mono-16bit wave file of just me speaking with very long pauses, it just detects the entire file to be voiced, and the voiced output chunk-00.wav is the entire audio file.

Any help is greatly appreciated. Below I have given the console output that I receive.

...

ANSWER

Answered 2022-Jan-31 at 11:45

I think I have found an alternative method of how to get VAD data. Instead of trying to get VAD from the pre-defined method shown in the link above, I create my own function.

The function basically measures the amplitude of the wave and any sharp spike observed above the base noise level (1.6x the base value) is taken to mean a voiced activity. This function assumes that only 1 human is speaking and that the noise level remains relatively constant.

Source https://stackoverflow.com/questions/70751218

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

Vulnerabilities

No vulnerabilities reported

Install VAD-python

You can download it from GitHub.
You can use VAD-python 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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