用于环境声音分类的二维比例-频率图半nmf

Wen-Chi Hsieh, Chin-Wen Ho, Viet-Hang Duong, Yuan-Shan Lee, Jia-Ching Wang
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引用次数: 1

摘要

提出了一种新的基于比例-频率映射的二维半非负矩阵分解(2D Semi-NMF)的环境声分类二维特征提取方法。我们首先从输入信号中提取比例-频率映射(SFMs),并认为该特征保留了信号的比例和频率特征。其次,将二维半nmf方法应用于SFMs,以获得更多的输入信号信息。我们使用从2D Semi-NMF中提取的组合系数进行分类。在8类环境声数据库上的实验结果表明,二维半NMF比传统的ID NMF和二维NMF具有更好的分类精度,并且在SFMs上应用二维半NMF比单独使用SFMs特征有略高的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
2D semi-NMF of scale-frequency map for environmental sound classification
This paper introduces a novel two dimensional feature extraction method for environmental sound classification, based on two dimensional semi-nonnegative matrix factorization (2D Semi-NMF) of scale-frequency maps. We first extract scale-frequency maps (SFMs) from the input signals, and this feature is considered preserving scale and frequency characteristics of signals. Second, a 2D Semi-NMF method is applied on SFMs to get more information of the input signals. We use the combinational coefficients extracted from 2D Semi-NMF for classification. Experimental results on an 8 class environmental sound database show that 2D Semi-NMF has better classification accuracy than traditional ID NMF and 2D NMF Also, applying 2D Semi-NMF on SFMs will get slightly improvement than SFMs features alone.
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