Event detection in short duration audio using Gaussian Mixture Model and Random Forest Classifier

Anurag Kumar, R. Hegde, Rita Singh, B. Raj
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引用次数: 11

Abstract

The amount of online multimedia files is increasing day by day with the ever increasing popularity of video sharing websites. This has led to a huge interest in content analysis of multimedia files. Audio being a major component of multimedia has the potential to help analyze different events occurring in a multimedia recording. In this paper we present an audio event detection mechanism based on Gaussian Mixture Model (GMM) and Random Forest Classifier. Experiments show that our proposed mechanism shows significant improvement in detection of specifically finer audio events in short duration recordings.
基于高斯混合模型和随机森林分类器的短时间音频事件检测
随着视频分享网站的日益普及,网络多媒体文件的数量日益增加。这导致了对多媒体文件内容分析的巨大兴趣。音频作为多媒体的主要组成部分,有可能帮助分析多媒体记录中发生的不同事件。本文提出了一种基于高斯混合模型和随机森林分类器的音频事件检测机制。实验表明,我们提出的机制在检测短时间录音中特别精细的音频事件方面有显着改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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