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author:

Wei, Jing-Ming (Wei, Jing-Ming.) [1] | Li, Ying (Li, Ying.) [2] (Scholars:李应)

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EI Scopus

Abstract:

Traditional approaches to environmental sounds recognition used acoustic features merely based on time domain or frequency domain. In this paper, a new feature descriptor that uses image texture information is proposed to identify specific environmental sounds based on the recognition of fixed-duration sounds segments where their corresponding spectrums are viewed as gray-level images. The proposed specific environmental sounds recognition system firstly conducts short-time spectrum estimation algorithm to the noisy sounds segments, and then extracts 5 time-frequency texture features descriptors(TFD) from the enhanced spectrum using sum and difference histogram (SDH), in the last place, applies random forest(RF) to make classification and recognition. The average recognition rate is 92.5% for 51 kinds of environmental sounds, outperforming the well-known MFCC features; meanwhile, it is robust to noise. © 2013 IEEE.

Keyword:

Decision trees Frequency domain analysis Frequency estimation Graphic methods Image segmentation Image texture Spectrum analysis Textures

Community:

  • [ 1 ] [Wei, Jing-Ming]College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 2 ] [Li, Ying]College of Mathematics and Computer Science, Fuzhou University, Fujian, China

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Year: 2013

Volume: 3

Page: 1277-1281

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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