基于关键事件检测及信息熵计算的音频场景分割

Key audio information always plays a critical role in high-level multi-media information analysis, index and retrieval. Based on key audio event detection and audio scene segmentation in an input audio stream, high-level semantic reference can be automatically carried out in various content-based analysis applications. However, most previous researches are focused on the detection and classification of single audio events, as to that of multi-media information, such as movies which consist of relatively complicated content, are not efficient. When processing a complex audio scene where several key audio events occur simultaneously, the existing methods shows obvious limitations. In this paper, we propose a novel audio scene segmentation algorithm based on the calculation of information entropy and the detection of key audio events in audio signals. The end points of audio scenes can be determined by IEC-ED.