원문정보
초록
영어
Accurate audio segmentation has recently received increasing attention for its applications in automatic indexing, content analysis and information retrieval. Hence, this paper proposes a highly accurate audio segmentation methodology using a genetic algorithm-based approach to adapting and optimizing segmentation window lengths. Specifically, this paper analyzes the parameter sequence of the root-mean-square values of an input audio stream with optimal sliding window (or segmentation window) lengths found and adapted by a genetic algorithm. In addition, this paper determines whether an audio-cut occurs or not by utilizing the parameter sequences as inputs of a support vector machine. Experimental results indicate that the proposed approach achieves 100.00% and 98.69% in the average precision and recall rates of segmentation performance, respectively.
목차
1. Introduction
2. Background Information
2.1. Support Vector Machine (SVM)
2.2. Genetic Algorithm (GA)
3. Proposed Audio Segmentation Methodology
4. Experimental Results
5. Conclusions
Acknowledgements
References
저자정보
참고문헌
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