Probabilistic vector mapping with trajectory information for noise-robust speech recognition

Abstract

The authors propose a probabilistic vector mapping method with trajectory information for noise-robust speech recognition. The proposed method estimates a speech vector using not only the current noisy vector but also adjacent vectors in the form of a trajectory pattern. According to our isolated word recognition experiment, the new method yields a better recognition rate than the probabilistic vector mapping method previously proposed.