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

Gabriel Meseguer-Brocal 1 Geoffroy Peeters 1 Guillaume Pellerin 1 Michel Buffa 2 Elena Cabrio 2 Catherine Faron Zucker 2, 3 Alain Giboin 2 Isabelle Mirbel 2 Romain Hennequin 4 Manuel Moussallam 4 Francesco Piccoli 4 Thomas Fillon 1
1 IRCAM - Institut de Recherche et Coordination Acoustique/Musique
2 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
3 I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis
4 Deezer R&D
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.
Keywords : Audio Analysis Audio Music Lyrics analysis WebAudio Semantic Web Database Knowledge base
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Submitted on : Tuesday, September 19, 2017 - 11:24:40 AM
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  • HAL Id : hal-01589250, version 1

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UNICE | IRCAM | WIMMICS | I3S | INRIA2017 | INRIA | UNIV-COTEDAZUR

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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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Université Nice Sophia Antipolis (UNS) Observatoire de la Côte d’Azur (OCA) Centre national de la recherche scientifique (CNRS) Institut national de la recherche en informatique et en automatique (Inria) SKEMA Business School EDHEC Business School  Centre Hospitalier Universitaire de Nice (CHU Nice) Centre National de Création Musicale (CIRM)  Ecole Nationale Supérieure d’Art Villa Arson Ecole Supérieure de Réalisation Audiovisuelle (ESRA) The Sustainable Design School (SDS) Ecole Supérieure de Danse de Cannes Rosella Hightower Conservatoire National à Rayonnement Régional de Nice (CNRR)