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Authors: Silvana Cunha Costa 1 ; Benedito G. Aguiar Neto 2 ; Joseana Macêdo Fechine 3 and Menaka Muppa 4

Affiliations: 1 Federal Center of Techological Education of Paraíba-CEFET-PB, Federal University of Campina Grande-UFCG, Brazil ; 2 Federal University of Campina Grande-UFCG, Intitute of Technology of Washington, University of Washington, United States ; 3 Federal University of Campina Grande-UFCG, Brazil ; 4 Intitute of Technology of Washington -University of Washington Tacoma, United States

ISBN: 978-989-8111-18-0

Keyword(s): Acoustic voice analysis, speech processing, acoustic features, cepstral parameters, disordered voices, speech pathology.

Related Ontology Subjects/Areas/Topics: Acoustic Signal Processing ; Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: Digital signal processing techniques have been used to perform an acoustic analysis for vocal quality assessment due to the simplicity and the non-invasive nature of the measurement procedures. Their employment is of special interest, as they can provide an objective diagnosis of pathological voices, and may be used as complementary tool in laryngoscope exams. The acoustic modeling of pathological voices is very important to discriminate normal and pathological voices. The degree of reliability and effectiveness of the discriminating process depends on the appropriate acoustic feature extraction. This paper aims at specifying and evaluating the acoustic features for vocal fold edema through a parametric modeling approach based on the resonant structure of the human speech production mechanism, and a nonparametric approach related to human auditory perception system. For this purpose, LPC and LPC-based cepstral coefficients, and mel-frequency cepstral coefficients are used. A vector-qu antizing-trained distance classifier is used in the discrimination process. (More)

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Paper citation in several formats:
Cunha Costa S.; G. Aguiar Neto B.; Macêdo Fechine J.; Muppa M. and (2008). SHORT-TERM CEPSTRAL ANALYSIS APPLIED TO VOCAL FOLD EDEMA DETECTION.In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 110-115. DOI: 10.5220/0001066901100115

@conference{biosignals08,
author={Silvana {Cunha Costa} and Benedito {G. Aguiar Neto} and Joseana {Macêdo Fechine} and Menaka Muppa},
title={SHORT-TERM CEPSTRAL ANALYSIS APPLIED TO VOCAL FOLD EDEMA DETECTION},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={110-115},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001066901100115},
isbn={978-989-8111-18-0},
}

TY - CONF

JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008)
TI - SHORT-TERM CEPSTRAL ANALYSIS APPLIED TO VOCAL FOLD EDEMA DETECTION
SN - 978-989-8111-18-0
AU - Cunha Costa, S.
AU - G. Aguiar Neto, B.
AU - Macêdo Fechine, J.
AU - Muppa, M.
PY - 2008
SP - 110
EP - 115
DO - 10.5220/0001066901100115

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