Reducing computational load in segmental hidden Markov model decoding for speech recognition
Research output: Contribution to journal › Article
Colleges, School and Institutes
Segment models have the potential to improve automatic speech recognition accuracy but with increased computational load. Two techniques which reduce this load are described: segmental beam pruning, and duration pruning. Experiments show that they can combine to give a 95% reduction in segment probability computations at a cost of a 3% increase in phone error rate.
|Number of pages||2|
|Publication status||Published - 1 Dec 2005|