Abstract
A system for speaker-independent connected digit recognition is described in which explicit acoustic-phonetic features and constraints play a significant role. The digit vocabulary is modeled using a finite-state pronunciation network whose branches correspond to meaningful acoustic-phonetic units. Each branch is associated with an acoustic pattern matcher which employs a combination of whole-spectrum and feature-based metrics. The system has been evaluated using 17 000 utterances from the Texas Instruments (TI) multidialect, connected digits database. The best configurations of the recognizer achieve string recognition accuracies of approximately 96 and 97 percent when the length of the input string is unknown and known, respectively, and when different talkers are used for training and testing.
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