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Automatic selection of acoustic prototypes is an important step towards making speech recognition systems automatically adaptable to new speakers. Two methods for automatically obtaining a set of acoustic prototypes for use by a centisecond labeling acoustic processor are described. One method is based on bootstrapping, the other on clustering. Recognition results using these automatically obtained prototypes on the 1000-word vocabulary natural language Laser Patent task are presented. These results are compared to those from an experiment in which the acoustic prototypes were manually selected.
Nádas et al. (Thu,) studied this question.