Emotion recognition from speech by combining databases and fusion of classifiers

Emotion recognition from speech by combining databases and fusion of classifiers

Lefter, I.
Rothkrantz, L.J.M.
Wiggers, P.
van Leeuwen, D.A.
TNO Defensie en Veiligheid

2010

We explore possibilities for enhancing the generality, portability and robustness of emotion recognition systems by combining data-bases and by fusion of classifiers. In a first experiment, we investigate the performance of an emotion detection system tested on a certain database given that it is trained on speech from either the same database, a different database or a mix of both. We observe that generally there is a drop in performance when the test database does not match the training material, but there are a few exceptions. Furthermore, the performance drops when a mixed corpus of acted databases is used for training and testing is carried out on real-life recordings. In a second experiment we investigate the effect of training multiple emotion detectors, and fusing these into a single detection system. We observe a drop in the Equal Error Rate (eer) from 19.0 % on average for 4 individual detectors to 4.2 % when fused using FoCal [1]. © 2010 Springer-Verlag Berlin Heidelberg.

Psychology
Detection system
Emotion detection
Emotion recognition
Equal error rate
Fusion of classifiers
Training and testing
Training material
Classifiers
Database systems
Detectors
Drops
Speech recognition

http://resolver.tudelft.nl/uuid:48bc9d48-b99b-42ee-8629-22c6ceb394c7

https://doi.org/10.1007/978-3-642-15760-8_45

425140

3642157599

0302-9743

13th International Conference on Text, Speech and Dialogue, TSD 2010, 6 September 2010 through 10 September 2010, Brno. Conference code: 82076, 6231 LNAI, 353-360

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

conference paper