10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Detecting Changes in Speech Expressiveness in Participants of a Radio Program

Plínio A. Barbosa

State University of Campinas, Brazil

A method for speech expressiveness change detection is presented which combines a dimensional analysis of speech expression, a Principal Component Analysis technique, as well as multiple regression analysis. From the three inferred rates of activation, valence, and involvement, two PCA-factors explain 97% of the variance of the judges’ evaluations of a corpus of radio show interaction. The multiple regression analysis predicted the values of the two listener-oriented, PCA-derived dimensions of promptness and empathy from the acoustic parameters automatically obtained from a set of 206 utterances produced by radio show’s participants. Analysed chronologically, the utterances reveal expression change from automatic acoustic analysis.

Full Paper     Multimedia Files

Bibliographic reference.  Barbosa, Plínio A. (2009): "Detecting changes in speech expressiveness in participants of a radio program", In INTERSPEECH-2009, 2155-2158.