Dynamic time warping applied to detection of confusable word pairs in automatic speech recognition

Abstract

In this paper we present a rnethod to predict if two words are likely to be confused by an Autornatic SpeechRecognition (ASR) systern. This method is based on the c1assical Dynamic Time Warping (DTW) technique. This technique, which is usually used in ASR to measure the distance between two speech signals, is usedhere to calculate the distance between two words. With this distance the words are c1assified as confusable or not confusable using a threshold. We have tested the methodin ac1assicalfalse acceptance/false rejection framework and the Equal Error Rate (EER) was measured to be less than 3%.