automatic-melody-harmonization-with-attention | A software to harmonize melodies with chords
kandi X-RAY | automatic-melody-harmonization-with-attention Summary
kandi X-RAY | automatic-melody-harmonization-with-attention Summary
automatic-melody-harmonization-with-attention is a Python library. automatic-melody-harmonization-with-attention has no bugs, it has no vulnerabilities and it has low support. However automatic-melody-harmonization-with-attention build file is not available. You can download it from GitHub.
TensorFlow implementation of a LSTM encoder decoder with attention (over a keyboard) to harmonize melodies with chords. It works with the Nottingham MIDI dataset in major or minor key.
TensorFlow implementation of a LSTM encoder decoder with attention (over a keyboard) to harmonize melodies with chords. It works with the Nottingham MIDI dataset in major or minor key.
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automatic-melody-harmonization-with-attention has a low active ecosystem.
It has 6 star(s) with 0 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
automatic-melody-harmonization-with-attention has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of automatic-melody-harmonization-with-attention is current.
Quality
automatic-melody-harmonization-with-attention has no bugs reported.
Security
automatic-melody-harmonization-with-attention has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
automatic-melody-harmonization-with-attention 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.
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automatic-melody-harmonization-with-attention releases are not available. You will need to build from source code and install.
automatic-melody-harmonization-with-attention 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 automatic-melody-harmonization-with-attention and discovered the below as its top functions. This is intended to give you an instant insight into automatic-melody-harmonization-with-attention implemented functionality, and help decide if they suit your requirements.
- Process MIDI files in a folder
- Extract phonon data
- Process tab
- One hot melody
- Compute one - hot chord
- Attaches n - play attention
- Add summaries for a variable
- Extract data from a DataFrame
- Train the model
- Add an argument group to the parser
- Get configuration
Get all kandi verified functions for this library.
automatic-melody-harmonization-with-attention Key Features
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automatic-melody-harmonization-with-attention Examples and Code Snippets
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Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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No vulnerabilities reported
Install automatic-melody-harmonization-with-attention
You can download it from GitHub.
You can use automatic-melody-harmonization-with-attention 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 automatic-melody-harmonization-with-attention 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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