Automatic classification of oral/nasal snoring sounds based on the acoustic properties

Snoring was once regarded as an indication of good sleep. But recently it has been known to be one of the symptoms which indicate sleep disordered breathing such as sleep apnea syndrome. Moreover, heavy snoring caused by oral breathing sometimes leads benign snorers to be apneics. Thus, it is important to detect oral snoring for medical treatment in the earlier stage, but we cannot know our own snoring. This paper describes a method to detect oral snoring by extracting the acoustic properties of snoring sounds and using the k-Nearest Neighbor classifier. As a result, over 92% of snoring sounds are successfully classified under the various cross validation evaluations.