PNCC | A implementation of Power Normalized Cepstral Coefficients | Speech library

by supikiti Python Version: Current License: MIT

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

kandi X-RAY | PNCC Summary

PNCC is a Python library typically used in Artificial Intelligence, Speech, Deep Learning applications. PNCC has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

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Support

Quality

Security

License

Reuse

Support

PNCC has a low active ecosystem.

It has 43 star(s) with 8 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 3 have been closed. On average issues are closed in 129 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PNCC is current.

Quality

PNCC has 0 bugs and 0 code smells.

Security

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

PNCC code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PNCC is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

Build file is available. You can build the component from source.

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

PNCC saves you 39 person hours of effort in developing the same functionality from scratch.

It has 105 lines of code, 10 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Compute the PCFT of an audio waveform
Calculate temporal masking of a rectified signal
R Implements asymmetric law filter filtering
Calculate the mean power normalization
Calculate spectral weight smoothing
Calculates the time power of a power signal
Checks if an excitation or non - excitation may occur
The halfwave rectification
R Calculate time - frequency normalization
Return the nonlinearity of a power function

Get all kandi verified functions for this library.

PNCC Key Features

No Key Features are available at this moment for PNCC.

PNCC Examples and Code Snippets

No Code Snippets are available at this moment for PNCC.

Community Discussions

Trending Discussions on PNCC

Install NDIS filer driver unbinded

QUESTION

Install NDIS filer driver unbinded

Asked 2020-Mar-24 at 19:38

I have built the "NDIS 6.0 Filter Driver" WinDDK sample (ndislwf.sys), and built the BindView sample to install "NDIS 6.0 Filter Driver". It installs OK, but it always bound to all Network Interfaces by default. Is it possible to install NDIS Filter Driver and have it unbound from all Network Interfaces so then I could bind it only to certain interfaces ?

The code from BindView uses SetupCopyOEMInfW to copy the driver to the OemInfs :

...

ANSWER

Answered 2020-Mar-24 at 19:38

Recent versions of Windows 10 have a feature for this. Put this line into your INF:

Source https://stackoverflow.com/questions/60644940

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

Vulnerabilities

No vulnerabilities reported

Install PNCC

You can download it from GitHub.
You can use PNCC 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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