Performance improvement in a dynamic-programming-based isolated word recognition system for the alpha-digit task

In isolated word recognition, the alpha-digit vocabulary has been recognized as one of the most difficult due to the acoustic similarities of the lexical entries. The purpose of this study is two-fold: a) To see how a dynamic programming approach can be augmented with phonetic information to improve recognition accuracy of the alpha-digits; and b) To minimize computational requirements for the recognition task. Performance improvement is accomplished by dividing the vocabulary into subsets based on the syllabic patterns of the words and by emphasizing the consonant-vowel transitional regions of the words. This algorithm has been tested on 10 speakers, 5 male and 5 female. The division of the vocabulary results in a substantial savings in computation with essentially no decrease in recognition accuracy. In addition to computational savings, emphasizing the transitional portions of the word in some cases results in accuracy improvement. Discussion of the results and suggestions for further improvement are presented.