Real time speaker indexing based on subspace method - application to TV news articles and debate

Abstract

In this paper, we propose a method to extract and verify in-dividual speaker utterance using a subspace method. This method can extract speech section of the same speaker by repeating speaker verification between the present speech section and the immediately previous speech section. The speaker models are automatically trained in the verification process without constructing speaker templates in advance. As a result, this speaker verification method is applied to speaker indexing. In this study, announcer utterances are automatically extracted from news speech data which in-cludes reporter or interviewer utterances. Also extracted automatically are the utterances of each participator in debate program broadcasted on TV.