Study on speaker-independent emotion recognition from speech on real-world data

This source preferred by Theodoros Kostoulas

This data was imported from DBLP:

Authors: Kostoulas, T., Ganchev, T. and Fakotakis, N.

Editors: Esposito, A., Bourbakis, N.G., Avouris, N.M. and Hatzilygeroudis, I.

https://doi.org/10.1007/978-3-540-70872-8

Volume: 5042

Pages: 235-242

Publisher: Springer

ISBN: 978-3-540-70871-1

This data was imported from Scopus:

Authors: Kostoulas, T., Ganchev, T. and Fakotakis, N.

Volume: 5042 LNAI

Pages: 235-242

ISBN: 9783540708711

DOI: 10.1007/978-3-540-70872-8_18

In the present work we report results from on-going research activity in the area of speaker-independent emotion recognition. Experimentations are performed towards examining the behavior of a detector of negative emotional states over non-acted/acted speech. Furthermore, a score-level fusion of two classifiers on utterance level is applied, in attempt to improve the performance of the emotion recognizer. Experimental results demonstrate significant differences on recognizing emotions on acted/real-world speech. © 2008 Springer Berlin Heidelberg.

The data on this page was last updated at 04:57 on May 24, 2019.