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| Paper: | AE-P6.10 |
| Session: | Audio for Multimedia and Networks |
| Time: | Friday, May 21, 13:00 - 15:00 |
| Presentation: |
Poster |
| Topic: |
Audio and Electroacoustics: Audio for Multimedia |
| Title: |
AUDIO SEGMENTATION BASED ON MULTI-SCALE AUDIO CLASSIFICATION |
| Authors: |
Yibin Zhang; Tsinghua University | | |
| | Jie Zhou; Tsinghua University | | |
| Abstract: |
Content-based audio segmentation plays an important role in multimedia applications. In order to segment accurately and on-line, most conventional algorithms are based on small-scale feature classification and always result in a high false alarm rate. Our experimental results show that large-scale audio can be more easily classified than small ones. According to this fact, we present a novel multi-scale framework for audio segmentation. First, a rough segmentation step based on large-scale classification is taken to ensure the integrality of the content of segments, which can avoid the consecutive audio belonging to the same kind being segmented into different pieces. Then a subtle segmentation step is taken to further locate the segmentation points for the boundary areas computed by the rough segmentation step. Experimental results show that a low false alarm rate can be achieved while preserving a low missing rate. |
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