Classification of affective speech within and across cultures
2013 (English)In: Frontiers in emotion scienceArticle in journal (Refereed) Published
Affect in speech is conveyed by patterns of pitch, intensity, voice quality and temporal features. The authors investigated how consistently emotions are expressed within and across cultures using a selection of 3,100 emotion portrayals from the VENEC corpus. The selection consisted of 11 emotions expressed with 3 levels of emotion intensity portrayed by professional actors from 5 different English speaking cultures (Australia, India, Kenya, Singapore, and USA). Classification experiments (nu-SVM) based on acoustic measures were performed in conditions where training and evaluation were conducted either within the same or different cultures and/or emotion intensities. Results first showed that average recall rates were 2.4-3.0 times higher than chance for intra- and inter-cultural conditions, whereas performance dropped 7-8 percentage units for cross-cultural conditions. This provides the first demonstration of an in-group advantage in cross-cultural emotion recognition using acoustic-feature-based classification. When further observed that matching the intensity level in training and testing data gave an advantage for high and medium intensity levels, but when classifying stimuli of unknown intensity the best performance was achieved with models trained on high intensity stimuli. Finally, classification performance across conditions varied as a function of emotion, with largest consistency for happiness, lust and relief. Implications for studies on cross-cultural emotion recognition and cross-corpora classification will be discussed.
Place, publisher, year, edition, pages
Computer Science Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:kth:diva-137383OAI: oai:DiVA.org:kth-137383DiVA: diva2:678928
tmh_import_13_12_13, tmh_id_3784. QC 201402212013-12-132013-12-132014-02-21Bibliographically approved