Publication Details
Enhancing multilingual recognition of emotion in speech by language identification
Matějka Pavel, Ing., Ph.D. (DCGM)
GAVRYUOKOVA, M.
Povolný Filip, Ing.
MARCHI, E.
SCHULLER, B.
multilingual emotion recognition, language identification, language families
We investigate, for the first time, if applying model selection based on automatic language identification (LID) can improve multilingual recognition of emotion in speech. Six emotional speech corpora from three language families (Germanic, Romance, Sino-Tibetan) are evaluated. The emotions are represented by the quadrants in the arousal/valence plane, i. e., positive/ negative arousal/valence. Four selection approaches for choosing an optimal training set depending on the current language are compared: within the same language family, across language family, use of all available corpora, and selection based on the automatic LID. We found that, on average, the proposed LID approach for selecting training corpora is superior to using all the available corpora when the spoken language is not known.
@inproceedings{BUT163404,
author="SAGHA, H. and MATĚJKA, P. and GAVRYUOKOVA, M. and POVOLNÝ, F. and MARCHI, E. and SCHULLER, B.",
title="Enhancing multilingual recognition of emotion in speech by language identification",
booktitle="17TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION - Proceedings (INTERSPEECH 2016)",
year="2016",
journal="Proceedings of Interspeech",
number="9",
pages="2949--2953",
publisher="International Speech Communication Association",
address="San Francisco",
doi="10.21437/Interspeech.2016-333",
issn="1990-9772",
url="https://www.isca-speech.org/archive/Interspeech_2016/pdfs/0333.PDF"
}