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Emotion in the singing voice-a deeper look at acoustic features in the light of automatic classification
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.ORCID iD: 0000-0002-1495-7773
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
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2015 (English)In: EURASIP Journal on Audio, Speech, and Music Processing, ISSN 1687-4714, E-ISSN 1687-4722, ISSN 1687-4714, 19Article in journal (Refereed) Published
Abstract [en]

We investigate the automatic recognition of emotions in the singing voice and study the worth and role of a variety of relevant acoustic parameters. The data set contains phrases and vocalises sung by eight renowned professional opera singers in ten different emotions and a neutral state. The states are mapped to ternary arousal and valence labels. We propose a small set of relevant acoustic features basing on our previous findings on the same data and compare it with a large-scale state-of-the-art feature set for paralinguistics recognition, the baseline feature set of the Interspeech 2013 Computational Paralinguistics ChallengE (ComParE). A feature importance analysis with respect to classification accuracy and correlation of features with the targets is provided in the paper. Results show that the classification performance with both feature sets is similar for arousal, while the ComParE set is superior for valence. Intra singer feature ranking criteria further improve the classification accuracy in a leave-one-singer-out cross validation significantly.

Place, publisher, year, edition, pages
Springer, 2015. 19
Keyword [en]
Emotion recognition, Singing voice, Acoustic features, Feature selection
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URN: urn:nbn:se:kth:diva-173992DOI: 10.1186/s13636-015-0057-6ISI: 000360837600001OAI: diva2:858214
EU, FP7, Seventh Framework Programme, 230331-PROPEREMOEU, European Research Council, 338164

QC 20151001. QC 20160221

Available from: 2015-10-01 Created: 2015-09-24 Last updated: 2016-02-21Bibliographically approved

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Salomao, Glaucia LaísSundberg, Johan
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Speech, Music and Hearing, TMH
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ReferencesLink to record
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