7th International Conference on Spoken Language Processing

September 16-20, 2002
Denver, Colorado, USA

Rapid Speaker Adaptation Using Speaker Clustering

Ernest J. Pusateri, Timothy J. Hazen

MIT Laboratory for Computer Science, USA

This paper examines an approach to speaker adaptation called speaker cluster weighting (SCW) for rapid adaptation in the Jupiter weather information system. SCW extends the ideas of previous speaker cluster techniques by allowing the speaker cluster models (learned from training data) to be adaptively weighted to match the current speaker. We explore strategies for automatic speaker clustering as well as cluster model training procedures for use with this algorithm. As part of this exploration, we develop a novel algorithm called least squares linear regression (LSLR) clustering for the clustering of speakers for whom only a small amount of data is available.


Full Paper

Bibliographic reference.  Pusateri, Ernest J. / Hazen, Timothy J. (2002): "Rapid speaker adaptation using speaker clustering", In ICSLP-2002, 61-64.