Structural Metadata Annotation of Speech Corpora: Comparing Broadcast News and Broadcast Conversations

Abstract

Structural metadata extraction (MDE) research aims to develop techniques for automatic conversion of raw speech recognition output to forms that are more useful to humans and to downstream automatic processes. It may be achieved by inserting boundaries of syntactic/semantic units to the flow of speech, labeling non-content words like filled pauses and discourse markers for optional removal, and identifying sections of disfluent speech. This paper compares two Czech MDE speech corpora, one in the domain of broadcast news and the other in the domain of broadcast conversations. A variety of statistics about fillers, edit disfluencies, and syntactic/semantic units are presented. In addition, it is reported that disfluent portions of speech show differences in the distribution of parts of speech (POS) of their content in comparison with the general POS distribution. The two Czech corpora are not only compared with each other, but also with available numbers relating to English MDE corpora of broadcast news and telephone conversations.

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