Improved speech recognition in noise

Recent enhancements to a connected speech recognition algorithm have led to substantial improvements in recognition accuracy especially for speech in noisy environments. The performance improvements are a direct result of three features of this algorithm: elimination of a priori speech endpoint detection; adaptation of templates for additive noise; and scoring using a likelihood ratio. Experimental results are provided which illustrate the improvements in recognition performance for both within-vocabulary substitution and out-of-vocabulary rejection.