Improved acoustic modeling with the SPHINX speech recognition system

The authors report recent efforts to further improve the performance of the SPHINX system for speaker-independent continuous speech recognition. They adhere to the basic architecture of the SPHINX system and use the DARPA resource management task and training corpus. The improvements are evaluated on the 600 sentences that comprise the DARPA February and October 1989 test sets. Several techniques that substantially reduced SPHINX´s error rate are presented. These techniques include dynamic features, semicontinuous hidden Markov models, speaker clustering, and the shared distribution modeling. The error rate of the baseline system was reduced by 45%