TY - CONF T1 - Acoustic Emotion Recognition using Dynamic Bayesian Networks and Multi-Space Distributions T2 - 10th Annual Conference of the Internacional Speech Communication Association (INTERSPEECH 2009) Y1 - 2009 A1 - Roberto Barra-Chicote A1 - Fernando Fernandez A1 - Syaheerah L. Lutfi A1 - Juan Manuel Lucas A1 - Javier Macias-Guarasa A1 - Juan Manuel Montero A1 - San Segundo, Ruben A1 - Jose Manuel Pardo KW - automatic emotion recognition KW - dynamic bayesian networks KW - emotion challenge KW - multi-space probability distribution AB -

In this paper we describe the acoustic emotion recognition
system built at the Speech Technology Group of the Universidad
Politecnica de Madrid (Spain) to participate in the INTERSPEECH
2009 Emotion Challenge. Our proposal is based on
the use of a Dynamic Bayesian Network (DBN) to deal with
the temporal modelling of the emotional speech information.
The selected features (MFCC, F0, Energy and their variants) are
modelled as different streams, and the F0 related ones are integrated
under a Multi Space Distribution (MSD) framework, to
properly model its dual nature (voiced/unvoiced). Experimental
evaluation on the challenge test set, show a 67.06% and 38.24%
of unweighted recall for the 2 and 5-classes tasks respectively.
In the 2-class case, we achieve similar results compared with
the baseline, with 8.5 times less features. In the 5-class case, we
achieve a statistically significant 6.5% relative improvement.

JF - 10th Annual Conference of the Internacional Speech Communication Association (INTERSPEECH 2009) PB - Internacional Speech Communication Association CY - Brighton, U.K. ER -