Importance

Loading Importance Indicators...

Abstract

Recognition of sound units is improved by comparing frame-pair feature vectors which helps compensate for context variations in the pronunciation of sound units. A plurality of reference frames are stored of reference feature vectors representing reference words. A linear predictive coder (10) generates a plurality of spectral feature vectors for each frame of the speech signals. A filter bank system (12) transforms the spectral feature vectors to filter bank representations. A principal feature vector transformer (14) transforms the filter bank representations to an identity matrix of transformed input feature vectors. A concatenate frame system (16) concatenates the input feature vectors of adjacent frames to form the feature vector of a frame-pair. A transformer (18) and a comparator (20) compute the likelihood that each input feature vector for a frame-pair was produced by each reference frame. This computation is performed individually and independently for each reference frame-pairs. A dynamic time warper (22) constructs an optimum time path through the input speech signals for each of the computed likelihoods. A high level decision logic (24) recognizes the input speech signals as one of the reference words in response to the computed likelihoods and the optimum time paths.

Loading the Abstract Image...

First Claim