SEVERE APNOEA DETECTION USING SPEAKER RECOGNITION TECHNIQUES

Ruben Fernández, Jose Luis Blanco, Luis A. Hernández, Eduardo López, José Alcazar, Doroteo T. Toledano

2009

Abstract

The aim of this paper is to study new possibilities of using Automatic Speaker Recognition techniques (ASR) for detection of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases can be very useful to give priority to their early treatment optimizing the expensive and time-consuming tests of current diagnosis methods based on full overnight sleep in a hospital. This work is part of an on-going collaborative project between medical and signal processing communities to promote new research efforts on automatic OSA diagnosis through speech processing technologies applied on a carefully designed speech database of healthy subjects and apnoea patients. So far, in this contribution we present and discuss several approaches of applying generative Gaussian Mixture Models (GMMs), generally used in ASR systems, to model specific acoustic properties of continuous speech signals in different linguistic contexts reflecting discriminative physiological characteristics found in OSA patients. Finally, experimental results on the discriminative power of speaker recognition techniques adapted to severe apnoea detection are presented. These results obtain a correct classification rate of 81.25%, representing a promising result underlining the interest of this research framework and opening further perspectives for improvement using more specific speech recognition technologies.

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Paper Citation


in Harvard Style

Fernández R., Blanco J., A. Hernández L., López E., Alcazar J. and T. Toledano D. (2009). SEVERE APNOEA DETECTION USING SPEAKER RECOGNITION TECHNIQUES . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 124-130. DOI: 10.5220/0001546601240130


in Bibtex Style

@conference{biosignals09,
author={Ruben Fernández and Jose Luis Blanco and Luis A. Hernández and Eduardo López and José Alcazar and Doroteo T. Toledano},
title={SEVERE APNOEA DETECTION USING SPEAKER RECOGNITION TECHNIQUES},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={124-130},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001546601240130},
isbn={978-989-8111-65-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
TI - SEVERE APNOEA DETECTION USING SPEAKER RECOGNITION TECHNIQUES
SN - 978-989-8111-65-4
AU - Fernández R.
AU - Blanco J.
AU - A. Hernández L.
AU - López E.
AU - Alcazar J.
AU - T. Toledano D.
PY - 2009
SP - 124
EP - 130
DO - 10.5220/0001546601240130