Mathieu Barthet

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Without a rich understanding of user behaviours and needs, music information retrieval (MIR) systems might not be ideally suited to their potential users. In this study, we followed an ethnographic methodology to elicit some of the strategies used by musicologists to explore and document musical performances, in order to investigate if and how technologies(More)
This paper presents preliminary work on musical instruments ontology design, and investigates heterogene-ity and limitations in existing instrument classification schemes. Numerous research to date aims at representing information about musical instruments. The works we examined are based on the well known Hornbostel and Sach's classification scheme. We(More)
Semantic Layer Projection (SLP) is a method for automatically annotating music tracks according to expressed mood based on audio. We evaluate this method by comparing it to a system that infers the mood of a given track using associated tags only. SLP differs from conventional auto-tagging algorithms in that it maps audio features to a low-dimensional(More)
The work presented here is part of a larger project directed toward a better understanding of the influence of timbre variations upon musical expressiveness. To address such an issue, we have limited our study to the relationship between the physics and playing of the clarinet, and the generated timbre. This reduction of the problem is justified by the fact(More)
—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(More)