Open Access Research

Semantic structures of timbre emerging from social and acoustic descriptions of music

Rafael Ferrer* and Tuomas Eerola

Author Affiliations

Finnish Centre of Excellence in Interdisciplinary Music Research, University of Jyväskylä, Jyväskylä, Finland

For all author emails, please log on.

EURASIP Journal on Audio, Speech, and Music Processing 2011, 2011:11  doi:10.1186/1687-4722-2011-11

Published: 7 December 2011

Abstract

The perceptual attributes of timbre have inspired a considerable amount of multidisciplinary research, but because of the complexity of the phenomena, the approach has traditionally been confined to laboratory conditions, much to the detriment of its ecological validity. In this study, we present a purely bottom-up approach for mapping the concepts that emerge from sound qualities. A social media (http://www.last.fm webcite) is used to obtain a wide sample of verbal descriptions of music (in the form of tags) that go beyond the commonly studied concept of genre, and from this the underlying semantic structure of this sample is extracted. The structure that is thereby obtained is then evaluated through a careful investigation of the acoustic features that characterize it. The results outline the degree to which such structures in music (connected to affects, instrumentation and performance characteristics) have particular timbral characteristics. Samples representing these semantic structures were then submitted to a similarity rating experiment to validate the findings. The outcome of this experiment strengthened the discovered links between the semantic structures and their perceived timbral qualities. The findings of both the computational and behavioural parts of the experiment imply that it is therefore possible to derive useful and meaningful structures from free verbal descriptions of music, that transcend musical genres, and that such descriptions can be linked to a set of acoustic features. This approach not only provides insights into the definition of timbre from an ecological perspective, but could also be implemented to develop applications in music information research that organize music collections according to both semantic and sound qualities.

Keywords:
timbre; natural language processing; vector-based semantic analysis; music information retrieval; social media