| Paper: | AE-P6.4 | ||
| 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-CUT DETECTION AND AUDIO-SEGMENT CLASSIFICATION USING FUZZY C-MEANS CLUSTERING | ||
| Authors: | Naoki Nitanda; Hokkaido University | ||
| Miki Haseyama; Hokkaido University | |||
| Hideo Kitajima; Hokkaido University | |||
| Abstract: | This paper proposes an audio-cut detection and audio-segment classification method using fuzzy c-means clustering. In the proposed method, the boundaries between two different audio signals, which are called audio-cuts, can be detected by the fuzzy c-means clustering. In the fuzzy c-means clustering, the fuzzy number represents the possibility that the audio-cut exists. Therefore, according to the possibility, qualified candidates for audio-cuts can be obtained even if audio effects such as fade-in, fade-out, etc. are included in the audio signal. The audio signal is segmented at the detected audio-cuts, and these segments are classified into the following five classes: silence, music, speech, speech with music background, and speech with noise background. This classification simultaneously deletes the wrongly detected audio-cuts. Consequently, we can obtain the accurate audio-cuts and the classification results. | ||
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