5th International Conference on Spoken Language Processing
In this work, we investigate modifications to a probabilistic segmentation algorithm to achieve a real-time, and pipelined capability for a segment-based speech recognizer. The existing algorithm used a Viterbi and backwards A* search to hypothesize phonetic segments. We were able to reduce the computational requirements of this algorithm by reducing the effective search space to acoustic landmarks, and were able to achieve pipelined capability by executing the A* search in blocks defined by reliably detected phonetic boundaries. The new algorithm produces 30% fewer segments, and improves TIMIT phonetic recognition performance by 2.4% over an acoustic segmentation baseline. We were also able to produce 30% fewer segments on a word recognition task in a weather information domain.
Bibliographic reference. Lee, Steven C. / Glass, James R. (1998): "Real-time probabilistic segmentation for segment-based speech recognition", In ICSLP-1998, paper 0594.