ProMo | Prososdy Morph : A python library | Speech library

by timmahrt Python Version: 2.0.0 License: MIT

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

kandi X-RAY | ProMo Summary

ProMo is a Python library typically used in Artificial Intelligence, Speech applications. ProMo has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install ProMo' or download it from GitHub, PyPI.

Prososdy Morph: A python library for manipulating pitch and duration in an algorithmic way, for resynthesizing speech.

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Quality

Security

License

Reuse

Support

ProMo has a low active ecosystem.

It has 35 star(s) with 18 fork(s). There are 8 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 79 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ProMo is 2.0.0

Quality

ProMo has 0 bugs and 0 code smells.

Security

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

ProMo code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ProMo 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

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

Deployable package is available in PyPI.

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

ProMo saves you 459 person hours of effort in developing the same functionality from scratch.

It has 1083 lines of code, 61 functions and 18 files.

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

Top functions reviewed by kandi - BETA

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

Compute the intensity of two data points
Raise ImportError if matplotlib is not installed
Plot the duration morphological evolution
Adds plateauAmount to the peak
Morph a range of values between two data arrays
Find the smallest difference between two values
Finds the indices of the closest mapping from from toVal
Make a relative sequence relative to the given sequence
Plot F0
Morph a list of data points into another
Morph multiple data points from one location to another
Make a list of timestamps
Convert a sequence of values into absolute paths
Apply quadratic interpolation
Raise ImportError if numpy
Plot two pitch tracks
Builds the textgrids of the textgrids
Morphs an interval tier into a new one
Merge a point tier into a new one
Creates a new Textgrid with the given ratio
Plot a single pitch track
Adjust spike height by height
Shift the accent
Integrate the accent into the pitch list
Creates a plot of the morphological model
Converts inputNum to a string

Get all kandi verified functions for this library.

ProMo Key Features

No Key Features are available at this moment for ProMo.

ProMo Examples and Code Snippets

No Code Snippets are available at this moment for ProMo.

Community Discussions

No Community Discussions are available at this moment for ProMo.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install ProMo

You can install using 'pip install ProMo' or download it from GitHub, PyPI.
You can use ProMo 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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