5th International Conference on Spoken Language Processing

Sydney, Australia
November 30 - December 4, 1998

Segmentation and Classification of Broadcast News Audio

Thomas Hain, Philip C. Woodland

Cambridge University, UK

Broadcast news audio data contains a wide variety of different speakers and audio conditions (channel and background noise). This paper describes a segmentation, gender detection and audio classification scheme for such data which aims to provide a speech recogniser with a stream of reasonably-sized segments, each from a single speaker and audio type while discarding non-speech data. Each segment is labelled as either narrow or wide band and from either a female or male speaker. The segmentation system has been evaluated on the DARPA 1997 broadcast news data set and detailed segmentation accuracy results are presented. It is shown that the speech recognition accuracy for these automatically derived segments is very nearly the same as that for manually segmented data.

Full Paper

Bibliographic reference.  Hain, Thomas / Woodland, Philip C. (1998): "Segmentation and classification of broadcast news audio", In ICSLP-1998, paper 0851.