Semantic Segmentation Of Music Audio Contents

TitleSemantic Segmentation Of Music Audio Contents
Publication TypeConference Paper
Year of Publication2005
Conference NameInternational Computer Music Conference
AuthorsOng, B., & Herrera P.
AbstractThis paper proposes a novel approach to detect structural changes in music audio signals and provides a way to separate the different “sections” of a piece, i.e. “intro”, “verse” or “chorus”. Herein, we divide the segment boundaries detection task into a two-phase process with each having different functionalities. In order to obtain appropriate structural boundaries, we propose a combination of low-level descriptors to be extracted from music audio signals. A database of 54 audio files (The Beatles’ songs) is used for evaluation on a mainstream popular music collection. The experiment results show that our approach has achieved 71% of accuracy and 79% of reliability in identifying structural boundaries in music audio signals. These measures indicate that the performance of our method improves the results reported in the still scarce literature that includes quantitative analyses.
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