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Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection
Dublin, Ireland June 23-June 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.8818th IEEE Symposium on Computer-Based ...
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P. G?mez, F. D?az, A. ?lvarez, K. Murphy, C. L?zaro, R. Mart?nez, V. Rodellar, "Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection," Computer-Based Medical Systems, IEEE Symposium on, pp. 41-46, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005.
 
 
BibTex
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@article{ 10.1109/CBMS.2005.88,
author = {P. G?mez and F. D?az and A. ?lvarez and K. Murphy and C. L?zaro and R. Mart?nez and V. Rodellar},
title = {Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection},
journal ={Computer-Based Medical Systems, IEEE Symposium on},
volume = {0},
year = {2005},
issn = {1063-7125},
pages = {41-46},
doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.88},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer-Based Medical Systems, IEEE Symposium on
TI - Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection
SN - 1063-7125
SP41
EP46
A1 - P. G?mez,
A1 - F. D?az,
A1 - A. ?lvarez,
A1 - K. Murphy,
A1 - C. L?zaro,
A1 - R. Mart?nez,
A1 - V. Rodellar,
PY - 2005
KW - null
VL - 0
JA - Computer-Based Medical Systems, IEEE Symposium on
ER -
 
P. G?mez, Campus de Montegancedo
F. D?az, Campus de Montegancedo
A. ?lvarez, Campus de Montegancedo
K. Murphy, Campus de Montegancedo
C. L?zaro, Campus de Montegancedo
R. Mart?nez, Campus de Montegancedo
V. Rodellar, Campus de Montegancedo
In recent years emphasis has been placed upon the early detection of voice pathologies by using the signal processing of voice to evaluate certain time and spectrum domain parameters which may infer the presence of pathology. The present work is aimed at establishing the suitability of these voice spectral parameters in fixing a clear distinction between pathologic and normophonic voice, and to further classify the specific patient?s pathology. Principal Component Analysis is used in parameter selection. Results for normal and pathological samples will be presented and discussed.
Citation:
P. G?mez, F. D?az, A. ?lvarez, K. Murphy, C. L?zaro, R. Mart?nez, V. Rodellar, "Principal Component Analysis of Spectral Perturbation Parameters for Voice Pathology Detection," cbms, pp.41-46, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005
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