TY - GEN
T1 - Analysis of speech signals among obstructive sleep apnea patients
AU - Zigel, Yaniv
AU - Tarasiuk, Ariel
AU - Goldshtein, Evgenia
PY - 2008/12/1
Y1 - 2008/12/1
N2 - 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.
AB - 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.
KW - Obstructive sleep apnea
KW - Speech processing
KW - Speech signals
UR - http://www.scopus.com/inward/record.url?scp=62749096815&partnerID=8YFLogxK
U2 - 10.1109/EEEI.2008.4736637
DO - 10.1109/EEEI.2008.4736637
M3 - Conference contribution
AN - SCOPUS:62749096815
SN - 9781424424825
T3 - IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings
SP - 760
EP - 764
BT - 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
T2 - 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
Y2 - 3 December 2008 through 5 December 2008
ER -