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WASABI: a Two Million Song Database Project with Audio and Cultural Metadata plus WebAudio enhanced Client Applications

Abstract : This paper presents the WASABI project, started in 2017, which aims at (1) the construction of a 2 million song knowledge base that combines metadata collected from music databases on the Web, metadata resulting from the analysis of song lyrics, and metadata resulting from the audio analysis, and (2) the development of semantic applications with high added value to exploit this semantic database. A preliminary version of the WASABI database is already on-line 1 and will be enriched all along the project. The main originality of this project is the collaboration between the algorithms that will extract semantic metadata from the web and from song lyrics with the algorithms that will work on the audio. The following WebAudio enhanced applications will be associated with each song in the database: an online mixing table, guitar amp simulations with a virtual pedal-board, audio analysis visualization tools, annotation tools, a similarity search tool that works by uploading audio extracts or playing some melody using a MIDI device are planned as companions for the WASABI database.
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Contributor : Michel Buffa Connect in order to contact the contributor
Submitted on : Tuesday, September 19, 2017 - 11:24:40 AM
Last modification on : Wednesday, February 2, 2022 - 2:16:06 PM


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  • HAL Id : hal-01589250, version 1



Gabriel Meseguer-Brocal, Geoffroy Peeters, Guillaume Pellerin, Michel Buffa, Elena Cabrio, et al.. WASABI: a Two Million Song Database Project with Audio and Cultural Metadata plus WebAudio enhanced Client Applications. Web Audio Conference 2017 – Collaborative Audio #WAC2017, Queen Mary University of London, Aug 2017, London, United Kingdom. ⟨hal-01589250⟩



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