Recognizing emotions in dialogue with disfluences and non-verbal vocalisations

Leimin Tian, Catherine Lai, Johanna Moore

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We investigate the usefulness of DISfluencies and Non-verbal Vocalisations (DIS-NV) for recognizing human emotions in dialogues. The proposed features measure filled pauses, fillers, stutters, laughter, and breath in utterances. The predictiveness of DIS-NV features is compared with lexical features and state-of-the-art low-level acoustic features. Our experimental results show that using DIS-NV features alone is not as predictive as using lexical or acoustic features. However, adding them to lexical or acoustic feature set yields improvement compared to using lexical or acoustic features alone. This indicates that disfluencies and non-verbal vocalisations provide useful information overlooked by the other two types of features for emotion recognition.
Original languageEnglish
Title of host publicationProceedings of The 4th Interdisciplinary Workshop on Laughter and other Non-Verbal Vocalisations in Speech
Pages39-41
Number of pages3
Publication statusPublished - 14 Apr 2015
EventThe 4th Interdisciplinary Workshop on Laughter and other Non-Verbal Vocalisations in Speech - University of Twente, Enschede, Netherlands
Duration: 14 Apr 201515 Apr 2015

Conference

ConferenceThe 4th Interdisciplinary Workshop on Laughter and other Non-Verbal Vocalisations in Speech
CountryNetherlands
CityEnschede
Period14/04/1515/04/15

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