NDLI: Classifying the speech response of the brain using Gaussian hidden markov model (HMM) with independent component analysis (ICA)

Content Provider	IEEE Xplore Digital Library
Author	Jongin Kim Suh-Kyung Lee Boreom Lee
Copyright Year	2013
Description	Author affiliation: Dept. of Med. Syst. Eng. (DMSE), Gwangju Inst. of Sci. & Technol. (GIST), Gwangju, South Korea (Jongin Kim; Suh-Kyung Lee; Boreom Lee)
Abstract	The purpose of this paper is to determine whether electroencephalograpy (EEG) can be used as a tool for hearing impairment tests such as hearing screening. For this study, we recorded EEG responses to two syllables, /a/ and /u/, in Korean from three subjects at Gwangju Institute of Science and Technology. The ultimate goal of this study is to classify speech sound data regardless of their size using EEG; however, as an initial stage of the study, we classified only two different speech syllables using Gaussian hidden markov model. The result of this study shows a possibility that EEG could be used for hearing screening and other diagnostic tools related to speech perception.
Starting Page	4291
Ending Page	4294
File Size	682251
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610494
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Hidden Markov models Speech Noise Brain modeling Support vector machine classification Accuracy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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