Automatic speech summarization applied to English broadcast news speech

Abstract

This paper reports an automatic speech summarization method and experimental results using English broadcast news speech. In our proposed method, a set of words maximizing a summarization score indicating an appropriateness of summarization is extracted from automatically transcribed speech. This extraction is performed using a Dynamic Programming (DP) technique according to a target compression ratio. We have previously tested the performance of our method using Japanese broadcast news speech. Since our method is based on a statistical approach, it could be applied to any language. In this paper, English broadcast news speech transcribed using a speech recognizer is automatically summarized. In order to apply our method to English, the model of estimating word concatenation probabilities based on a dependency structure in the original speech given by a Stochastic Dependency Context Free Grammar (SDCFG) is modified. A summarization method for multiple utterances using two-level DP technique is also proposed.