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Speech emotion recognition using affective saliency

Chorianopoulou Arodami, Koutsakis Polychronis, Potamianos Alexandros

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URIhttp://purl.tuc.gr/dl/dias/2B1694B7-F7A0-4314-A57A-C9FF41F19F83-
Identifierhttps://www.isca-speech.org/archive/Interspeech_2016/abstracts/1311.html-
Identifierhttps://doi.org/10.21437/Interspeech.2016-1311-
Languageen-
Extent5 pagesen
TitleSpeech emotion recognition using affective saliencyen
CreatorChorianopoulou Arodamien
CreatorΧωριανοπουλου Αροδαμηel
CreatorKoutsakis Polychronisen
CreatorΚουτσακης Πολυχρονηςel
CreatorPotamianos Alexandrosen
CreatorΠοταμιανος Αλεξανδροςel
PublisherInternational Speech and Communication Associationen
Content SummaryWe investigate an affective saliency approach for speech emotion recognition of spoken dialogue utterances that estimates the amount of emotional information over time. The proposed saliency approach uses a regression model that combines features extracted from the acoustic signal and the posteriors of a segment-level classifier to obtain frame or segment-level ratings. The affective saliency model is trained using a minimum classification error (MCE) criterion that learns the weights by optimizing an objective loss function related to the classification error rate of the emotion recognition system. Affective saliency scores are then used to weight the contribution of frame-level posteriors and/or features to the speech emotion classification decision. The algorithm is evaluated for the task of anger detection on four call-center datasets for two languages, Greek and English, with good results. en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-11-08-
Date of Publication2016-
SubjectAffective saliencyen
SubjectEmotion recognitionen
SubjectFusion over timeen
SubjectSpoken dialogue systemsen
Bibliographic CitationA. Chorianopoulou, P. Koutsakis and A. Potamianos, "Speech emotion recognition using affective saliency," in 17th Annual Conference of the International Speech Communication Association, 2016, pp. 500-504. doi: 10.21437/Interspeech.2016-1311en

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