Quint-e/equivariant-self-supervision-tempo
Official implementation of "Equivariant Self-Supervision for Musical Tempo Estimation (ISMIR 2022)"
This project helps music professionals automatically determine the tempo of musical pieces. It takes audio files from various datasets as input and outputs precise tempo annotations, which can then be used to analyze music collections. It's ideal for musicologists, DJs, music catalog managers, or anyone needing to categorize or work with music based on its beats per minute.
No commits in the last 6 months.
Use this if you need to accurately estimate the tempo of large collections of audio tracks for analysis, categorization, or creative purposes.
Not ideal if you're looking for a simple drag-and-drop application without any technical setup, as this project requires some command-line interaction.
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26
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Language
Python
License
ISC
Category
Last pushed
Feb 06, 2023
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