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Genre-adaptive semantic computing and audio-based modelling for music mood annotation.

Saari, Pasi and Fazekas, Gyorgy and Eerola, Tuomas and Barthet, Mathieu and Lartillot, Olivier and Sandler, Mark (2016) 'Genre-adaptive semantic computing and audio-based modelling for music mood annotation.', IEEE transactions on affective computing., 7 (2). pp. 122-135.

Abstract

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outperforms a semantic computing technique that does not exploit genre information, and ACTwg-SLPwg outperforms conventional techniques and other genre-adaptive alternatives. In particular, improvements in the prediction rates are obtained for the valence dimension which is typically the most challenging core affect dimension for audio-based annotation. The specificity of genre categories is not crucial for the performance of ACTwg-SLPwg. The study also presents analytical insights into inferring a concise tag-based genre representation for genre-adaptive music mood analysis.

Item Type:Article
Keywords:Music information retrieval, Mood prediction, Social tags, Semantic computing, Music genre, Genre-adaptive.
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1109/TAFFC.2015.2462841
Publisher statement:© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:28 July 2015
Date deposited:24 August 2015
Date of first online publication:30 July 2015
Date first made open access:No date available

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