huzaifakhan04/music-recommendation-web-application-based-on-rhythmic-similarity-using-locality-sensitive-hashing

This repository contains a web application that integrates with a music recommendation system, which leverages a dataset of 3,415 audio files, each lasting thirty seconds, utilising a Locality-Sensitive Hashing (LSH) implementation to determine rhythmic similarity, as part of an assignment for the Fundamental of Big Data Analytics (DS2004) course.

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This web application helps music enthusiasts and audio content creators find new songs that share a similar rhythm to an uploaded audio file. You provide a 30-second audio clip, and the system suggests both the most rhythmically similar and dissimilar songs from its library, helping you discover new music or identify tracks for specific rhythmic needs. This tool is designed for anyone interested in music discovery based purely on rhythmic patterns.

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Use this if you want to discover music or audio tracks that have a similar rhythmic feel to a specific 30-second audio input.

Not ideal if you are looking for music recommendations based on genre, lyrics, melody, instrumentation, or other non-rhythmic features.

music-discovery audio-analysis rhythm-matching content-creation music-curation
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Maturity 16 / 25
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Language

Jupyter Notebook

License

BSD-3-Clause

Last pushed

Mar 01, 2024

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