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Audio content analysis for online audiovisual data segmentation and classification (2001)
| Venue: | 62 IEEE SIGNAL PROCESSING MAGAZINE MARCH 2004 |
| Citations: | 109 - 6 self |
BibTeX
@INPROCEEDINGS{Zhang01audiocontent,
author = {Tong Zhang and C. -c. Jay Kuo},
title = {Audio content analysis for online audiovisual data segmentation and classification},
booktitle = {62 IEEE SIGNAL PROCESSING MAGAZINE MARCH 2004},
year = {2001},
pages = {441--457}
}
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Abstract
Abstract—While current approaches for audiovisual data segmentation and classification are mostly focused on visual cues, audio signals may actually play a more important role in content parsing for many applications. An approach to automatic segmentation and classification of audiovisual data based on audio content analysis is proposed. The audio signal from movies or TV programs is segmented and classified into basic types such as speech, music, song, environmental sound, speech with music background, environmental sound with music background, silence, etc. Simple audio features including the energy function, the average zero-crossing rate, the fundamental frequency, and the spectral peak tracks are extracted to ensure the feasibility of real-time processing. A heuristic rule-based procedure is proposed to segment and classify audio signals and built upon morphological and statistical analysis of the time-varying functions of these audio features. Experimental results show that the proposed scheme achieves an accuracy rate of more than 90 % in audio classification. Index Terms—Audio analysis, audio indexing, audio segmentation, audiovisual content parsing, information filtering and retrieval, multimedia database management. I.
Keyphrases
audio content analysis audio signal online audiovisual data segmentation music background environmental sound important role heuristic rule-based procedure many application accuracy rate time-varying function real-time processing statistical analysis visual cue audio classification audio indexing information filtering audio feature audiovisual data segmentation fundamental frequency energy function audio segmentation audiovisual content parsing index term audio analysis automatic segmentation tv program audiovisual data database management average zero-crossing rate spectral peak track basic type simple audio feature experimental result current approach
