Ninth International Conference on Spoken Language Processing

Pittsburgh, PA, USA
September 17-21, 2006

Analyzing Dialogue Data for Real-World Emotional Speech Classification

Ryuichi Nisimura, Souji Omae, Hideki Kawahara, Toshio Irino

Wakayama University, Japan

In order to obtain an understanding of the userís emotion in humanmachine dialogues, an analysis of dialogical utterances in the real world was performed. This work comprises three major steps. (1) The actual conditions of 16 basic emotions were evaluated using Japanese child voices, which were collected through the field test of the public spoken dialogue system. (2) Two factors were derived by a factor analysis. The factors were defined as fundamental psychological factors representing "delightful" and "hateable" emotions. (3) The relationships between the factors and the physical acoustic features were investigated to establish a capability to sense a userís mental state for the dialogue system. In the experimental discriminations between the delightful and hateable emotions, a correct rate of 98.8% was achieved in classifying childís utterances by the SVM (Support Vector Machine) with 11 acoustic features.

Full Paper

Bibliographic reference.  Nisimura, Ryuichi / Omae, Souji / Kawahara, Hideki / Irino, Toshio (2006): "Analyzing dialogue data for real-world emotional speech classification", In INTERSPEECH-2006, paper 1675-Wed2BuP.9.