A robust audio classification and segmentation method

Lie Lu, Hao Jiang, HongJiang Zhang
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引用次数: 240

Abstract

In this paper, we present a robust algorithm for audio classification that is capable of segmenting and classifying an audio stream into speech, music, environment sound and silence. Audio classification is processed in two steps, which makes it suitable for different applications. The first step of the classification is speech and non-speech discrimination. In this step, a novel algorithm based on KNN and LSP VQ is presented. The second step further divides non-speech class into music, environment sounds and silence with a rule based classification scheme. Some new features such as the noise frame ratio and band periodicity are introduced and discussed in detail. Our experiments in the context of video structure parsing have shown the algorithms produce very satisfactory results.
一种鲁棒音频分类和分割方法
在本文中,我们提出了一种鲁棒的音频分类算法,该算法能够将音频流分割和分类为语音,音乐,环境声音和沉默。音频分类分为两步处理,这使得它适合不同的应用。分类的第一步是言语和非言语区分。在这一步中,提出了一种基于KNN和LSP VQ的新算法。第二步采用基于规则的分类方案将非言语类进一步划分为音乐、环境声和沉默。介绍并详细讨论了噪声帧比和频带周期性等新特性。在视频结构分析的背景下进行的实验表明,该算法产生了令人满意的结果。
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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