Automatic segmentation of speakers in broadcast audio material

Hyoung-Gook Kim; Thomas Sikora

doi:10.1117/12.526080

18 December 2003 Automatic segmentation of speakers in broadcast audio material

Hyoung-Gook Kim; Thomas Sikora

Author Affiliations +

Proceedings Volume 5307, Storage and Retrieval Methods and Applications for Multimedia 2004; (2003) https://doi.org/10.1117/12.526080
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

In this paper, dimension-reduced, decorrelated spectral features for general sound recognition are applied to segment conversational speech of both broadcast news audio and panel discussion television programs. Without a priori information about number of speakers, the audio stream is segmented by a hybrid metric-based and model-based segmentation algorithm. For the measure of the performance we compare the segmentation results of the hybrid method versus metric-based segmentation with both the MPEG-7 standardized features and Mel-scale Frequency Cepstrum Coefficients (MFCC). Results show that the MFCC features yield better performance compared to MPEG-7 features. The hybrid approach significantly outperforms direct metric based segmentation.

Citation Download Citation

Hyoung-Gook Kim, Hyoung-Gook Kim, Thomas Sikora, Thomas Sikora, } "Automatic segmentation of speakers in broadcast audio material", Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); doi: 10.1117/12.526080; https://doi.org/10.1117/12.526080

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