A New Verification-based Fast Match Approach to Large Vocabulary Constinuous Speech Recognition

Acoustic fast match is usually used to accelerate search in large vocabulary continuous speech recognition. This paper discusses a new acoustic fast match algorithm. This proposed fast match is based on incremental evaluation of the score and the use of normalized likelihood scores. This is in contrast to more traditional fast matches where a likelihood score is used. In addition, streaming SIMD extensions (SSE) for Intel machine instructions are used for fast Gaussian calculation. Results on a 20K Japanese broadcast news task show that the proposed fast match leads to about 30% improvement in speed with a slight performance degradation.