Spectral-temporal receptive fields and MFCC balanced feature extraction for noisy speech recognition

Jia Ching Wang, Chang Hong Lin, En Ting Chen, Pao Chi Chang

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

3 Scopus citations

Abstract

This paper aims to propose a new set of acoustic features based on spectral-temporal receptive fields (STRFs). The STRF is an analysis method for studying physiological model of the mammalian auditory system in spectral-temporal domain. It has two different parts: one is the rate (in Hz) which represents the temporal response and the other is the scale (in cycle/octave) which represents the spectral response. With the obtained STRF, we propose an effective acoustic feature. First, the energy of each scale is calculated from the STRF. The logarithmic operation is then imposed on the scale energies. Finally, the discrete Cosine transform is applied to generate the proposed STRF feature. In our experiments, we combine the proposed STRF feature with conventional Mel frequency cepstral coefficients (MFCCs) to verify its effectiveness. In a noise-free environment, the proposed feature can increase the recognition rate by 17.48%. Moreover, the increase in the recognition rate ranges from 5% to 12% in noisy environments.

Original languageEnglish
Title of host publication2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9786163618238
DOIs
StatePublished - 12 Feb 2014
Event2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014 - Chiang Mai, Thailand
Duration: 9 Dec 201412 Dec 2014

Publication series

Name2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014

Conference

Conference2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
Country/TerritoryThailand
CityChiang Mai
Period9/12/1412/12/14

Keywords

  • Mel frequency cepstral coefficients
  • spectral-temporal receptive fields
  • speech recognition

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