Utterance Verification using an Optimized

Utterance verification can be seen as a conventional pattern classification problem in which a feature vector is obtained for each hypothesized word in order to classify it as either correct or incorrect. In this paper, we study the application to this problem of an optimized version of the -Nearest Neighbour decision rule which also incorporates an adequate feature selection technique. Experiments are reported showing that it gives comparatively good results.