An audio-scene cut detection method using fuzzy c-means algorithm for audio-visual indexing

This paper proposes an accurate audio-scene cut detection method. The audio-scene denotes a segment which is constructed of semantically correlated audio-shots, where the audio-shot is a smaller segment than the audio-scene; and the boundaries between two audio-scenes and that between two audio-shots are called the audio-scene cut and the audio-shot cut, respectively. Recently, high performance of audio-scene cut detection methods is required for the audio-visual indexing; and several detection methods have been proposed. However, since most of the methods segment the audio signal in a fixed time interval before indexing, the users cannot obtain the exact time of the audio-scene cuts. Therefore, we propose an accurate audio-scene cut detection method. We utilize the fuzzy c-means algorithm so that the reliability of the audio-shot cut is represented by the fuzzy number. Afterwards, the semantically correlated audio-shots are merged into the same audio-scene, and thereby the audio-scene cuts are obtained.