Analysis of speech signals among obstructive sleep apnea patients

Yaniv Zigel, Ariel Tarasiuk, Evgenia Goldshtein

Research output: Contribution to conferencePaperpeer-review

4 Scopus citations

Abstract

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder. Previous studies have confirmed that OSA is associated with anatomical abnormalities of the upper airways. Acoustic parameters of human speech are significantly influenced by the vocal tract structure and soft tissue properties; therefore, there is reason to believe that there is correlation between speech signal parameters and the existence of OSA. This work aims to explore the influence of OSA on acoustic speech features. Signal processing and pattern recognition algorithms were developed to differentiate between OSA and non-OSA subjects using their speech signals. Using Gaussian mixture model (GMM) classifier and a speech database of 13 non- OSA and 13 OSA diagnosed adult male subjects, an equal error rate (EER) of 7.7% was achieved. These results show that acoustic features from speech signals of awake subjects can predict OSA, and can be used as a tool for initial screening of potential patients.

Original languageEnglish
Pages760-764
Number of pages5
DOIs
StatePublished - 1 Dec 2008
Externally publishedYes
Event2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008 - Eilat, Israel
Duration: 3 Dec 20085 Dec 2008

Conference

Conference2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
Country/TerritoryIsrael
CityEilat
Period3/12/085/12/08

Keywords

  • Obstructive sleep apnea
  • Speech processing
  • Speech signals

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