Subband spectral histogram feature for improved sound recognition in low SNR conditions

Roneel V. Sharan, Tom J. Moir

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

2 Citations (Scopus)

Abstract

In this work, we use the subband intensity histogram values extracted from the spectrogram image of sound signals to form the feature vector for sound classification in an audio surveillance application. We propose two features based on this approach. Firstly, we extract the histogram features from the short time Fourier transform spectrogram image of sound signals, which we refer as the spectral histogram feature (SHF). Secondly, we apply the mel-filter to the spectrogram image before histogram feature extraction which we refer as the mel-spectral histogram feature (MSHF). When compared to baseline features from similar work, the SHF was shown to give significantly improved results in low SNR conditions with a higher overall classification performance. In addition, the MSHF produced even better results than the SHF with the added advantage of a lower feature dimension.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Digital Signal Processing, DSP 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages432-435
Number of pages4
Volume2015-September
ISBN (Electronic)9781479980581
DOIs
Publication statusPublished - 9 Sep 2015
Externally publishedYes
EventIEEE International Conference on Digital Signal Processing, DSP 2015 - Singapore, Singapore
Duration: 21 Jul 201524 Jul 2015

Conference

ConferenceIEEE International Conference on Digital Signal Processing, DSP 2015
CountrySingapore
CitySingapore
Period21/07/1524/07/15

Keywords

  • audio surveillance
  • mel-filter
  • sound recognition
  • spectral histogram feature
  • support vector machine

Fingerprint

Dive into the research topics of 'Subband spectral histogram feature for improved sound recognition in low SNR conditions'. Together they form a unique fingerprint.

Cite this