Abstract

In this paper several improvements of our speech-to-speech translation system JANUS on spontaneous human-to-human dialogs are presented. Common phenomena in spontaneous speech are described, followed by a classification of different types of noises. To handle the variety of spontaneous effects in human-to-human dialogs, special noise models are introduced representing both human and nonhuman noises, as well as word fragments. It will be shown that both the acoustic and the language modeling of these noises increase the recognition performance significantly. In the experiments, a clustering of the noise classes is performed and the resulting cluster variants are compared, thus allowing to determine the best tradeoff between sensitivity and trainability of the models. 1. INTRODUCTION Recently, a large number of studies has been devoted to the task of recognizing and understanding spontaneous speech. Compared to read speech, some specific problems exist when spontaneous speech is to be ...

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