Comparison of feature performance in gunshot detection depending on noise degradation

M. Hrabina, M. Sigmund
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引用次数: 6

Abstract

This paper compares three different features and various feature orders for the purpose of determining the best feature for gunshot detection under adverse noise condition. Compared features cover LPC, LPCC and MFCC with orders from 8 to 30. All features were extracted from sounds with the sound-to-noise ratios 30, 20, 10, and 0 dB. The background noise was simulated by white noise. Experimental results indicate that LPC coefficients are the most efficient features, especially for low noise. On the other hand, MFCC performed well in noisy environments at 10 dB and 20 dB.
基于噪声退化的枪弹检测特征性能比较
本文比较了三种不同的特征和不同的特征顺序,以确定在不利噪声条件下枪弹检测的最佳特征。比较功能包括LPC, LPCC和MFCC,订单从8到30。所有特征都是从声噪比分别为30、20、10和0 dB的声音中提取的。背景噪声用白噪声模拟。实验结果表明,LPC系数是最有效的特征,特别是在低噪声情况下。另一方面,MFCC在10 dB和20 dB的噪声环境下表现良好。
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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