13th Annual Conference of the International Speech Communication Association

Portland, OR, USA
September 9-13, 2012

Modulation Spectrum Analysis for Speaker Personality Trait Recognition

Alexei Ivanov, Xin Chen

Knowledge Technologies, Pearson, Menlo Park, CA, USA

We explore the utility of individually selected modulation spectral features for speech and speaker characterization in general, and specifically to prediction of the perceived speaker personality profile. We suggest a method of construction of a sparse feature space and a method of finding the approximately best feature subset for attributing a specific characteristic of speech or speaker. The current selection method is based on the Kolmogorov-Smirnov statistical test applied to individual features. We assume that the characterization task is defined empirically and no a-priory theory exist to explain characteristic attribution processes. Experimental results indicate that employment of selected modulation spectral features works better than the current state-of-the-art in prediction of personality traits.

Index Terms: speech characterization, modulation spectrum analysis, feature selection

Full Paper

Bibliographic reference.  Ivanov, Alexei / Chen, Xin (2012): "Modulation spectrum analysis for speaker personality trait recognition", In INTERSPEECH-2012, 278-281.