4th International Conference on Spoken Language Processing

Philadelphia, PA, USA
October 3-6, 1996

Recognizing Emotion in Speech

Frank Dellaert, Thomas Polzin, Alex Waibel

School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

This paper explores several statistical pattern recognition techniques to classify utterances according to their emotional content. We have recorded a corpus containing emotional speech with over a 1000 utterances from different speakers. We present a new method of extracting prosodic features from speech, based on a smoothing spline approximation of the pitch contour. To make maximal use of the limited amount of training data available, we introduce a novel pattern recognition technique: majority voting of subspace specialists. Using this technique, we obtain classification performance that is close to human performance on the task.

Full Paper

Bibliographic reference.  Dellaert, Frank / Polzin, Thomas / Waibel, Alex (1996): "Recognizing emotion in speech", In ICSLP-1996, 1970-1973.