Detecting pathological speech using contour modeling of harmonic-to-noise ratio

Jung Won Lee, Samuel Kim, Hong Goo Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

This paper proposes a new feature extraction method for automatically detecting pathological voice in a normal conversation scenario. Unlike conventional approaches that utilize the static harmonic-to-noise ratio (HNR) characteristics of sustained vowel, the proposed method considers the dynamic movements of articulatory organs depending on the types of phonations. Assuming those movements reflect the health status of subjects, the proposed method utilizes the characteristics of HNR contour within a single sentence-level speech signal. Experimental results show that the proposed method reduces the classification error rate by 35.2 % (relative) compared to the conventional method.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5969-5973
Number of pages5
ISBN (Print)9781479928927
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: 2014 May 42014 May 9

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period14/5/414/5/9

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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