Decision rules for speaker-independent isolated word recognition

This study compares the recognition rates attainable with the aid of two different methods of generating reference templates from training words and two different decision rules. The test enviroment consists of isolated words from a small vocabulary spoken by a large number of speakers over the public telephone system. Experiments performed show that the use of individual word templates for references together with the k-nearest neighbor decision procedure substantially improves the performance in isolated word recognition. We attempted to minimize the computations involved in the k-nearest neighbor decision procedure by assuming that the dynamic time-warp distance was a metric, which would allow use of a 1-nearest neighbor decision rule with appropriately relabeled reference data. Results indicate that this step leads to an error rate exceeding that obtainable with the 1-nearest neighbor rule on the original nonrelabeled data.