Effects of Audio Compression in Automatic Detection of Voice Pathologies

This paper investigates the performance of an automatic system for voice pathology detection when the voice samples have been compressed in MP3 format and different binary rates (160, 96, 64, 48, 24, and 8 kb/s). The detectors employ cepstral and noise measurements, along with their derivatives, to...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2008-12, Vol.55 (12), p.2831-2835
Main Authors: SÁenz-LechÓn, NicolÁs, Osma-Ruiz, VÍctor, Godino-Llorente, Juan I., Blanco-Velasco, Manuel, Cruz-RoldÁn, Fernando, Arias-LondoÑo, JuliÁn D.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Audio compression
Cepstral analysis
Channels
Compressed
Data Compression - methods
Derivatives
Detectors
Digital audio players
Fourier Analysis
Gaussian mixture models
Humans
MP3 compression
Multimedia
Narrowband
Noise measurement
Normal Distribution
Pathology
Pattern Recognition, Automated - methods
Recording
ROC Curve
Sound Spectrography - methods
Speech Acoustics
Support vector machine classification
Support vector machines
Telemedicine
Voice
Voice Disorders - diagnosis
Voice Disorders - physiopathology
voice pathology detection
Voice Quality
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper investigates the performance of an automatic system for voice pathology detection when the voice samples have been compressed in MP3 format and different binary rates (160, 96, 64, 48, 24, and 8 kb/s). The detectors employ cepstral and noise measurements, along with their derivatives, to characterize the voice signals. The classification is performed using Gaussian mixtures models and support vector machines. The results between the different proposed detectors are compared by means of detector error tradeoff (DET) and receiver operating characteristic (ROC) curves, concluding that there are no significant differences in the performance of the detector when the binary rates of the compressed data are above 64 kb/s. This has useful applications in telemedicine, reducing the storage space of voice recordings or transmitting them over narrow-band communications channels.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2008.923769