Automatic recognition of Korean broadcast news speech

Abstract

This paper describes preliminary results of automatic recognition of Korean broadcast-news speech. We have been working on flexible vocabulary isolated-word speech recognition, and the same HMM models are used for broadcast-news continuous speech recognition. The recognizer is trained by using phonetically balanced isolated words speech, rather than the broadcast news speech itself. In this research, we use several different lexica to investigate the recognition performance according to the length of the words. We also propose a long-distance bigram language model, which can be used at the first stage of the search, so that it can reduce the recognition errors caused by earlier pruning of correct hypothesis.