Title
An Integrated Solution For Snoring Sound Classification Using Bhattacharyya Distance Based Gmm Supervectors With Svm, Feature Selection With Random Forest And Spectrogram With Cnn
Abstract
Snoring is caused by the narrowing of the upper airway and it is excited by different locations within the upper airways. This irregularity could lead to the presence of Obstructive Sleep Apnea Syndrome (OSAS). Diagnosis of OSAS could therefore be made by snoring sound analysis. This paper proposes the novel method to automatically classify snoring sounds by their excitation locations for ComParE2017 challenge. We propose 3 sub-systems for classification. In the first system, we propose to integrate Bhattacharyya distance based Gaussian Mixture Model (GMM) supervectors to a set of static features provided by ComParE2017 challenge. The Bhattacharyya distance based GMM supervectors characterize the spectral dissimilarity measure among snore sounds excited by different locations. And, we employ Support Vector Machine (SVM) for classification. In the second system. we perform feature selection on static features provided by the challenge and conduct classification using Random Forest. In the third system, we extract spectrogram from audio and employ Convolutional Neural Network (CNN) for snore sound classification. Then, we fuse 3 sub-systems to produce final classification results. The experimental results show that the proposed system performs better than the challenge baseline.
Year
DOI
Venue
2017
10.21437/Interspeech.2017-1794
18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION
Keywords
Field
DocType
snore sound classification, GMM supervectors, computational paralinguistics
Bhattacharyya distance,Feature selection,Pattern recognition,Spectrogram,Computer science,Support vector machine,Sound classification,Speech recognition,Artificial intelligence,Random forest
Conference
ISSN
Citations 
PageRank 
2308-457X
2
0.38
References 
Authors
0
4
Name
Order
Citations
PageRank
Tin Lay Nwe147934.59
Tran Huy Dat216525.31
Wen Zheng Terence Ng321.40
Bin Ma460047.26