Title :
Sound quality indicating system using EEG and GMDH-type neural network
Author :
Nishimura, Kosuke ; Mitsukura, Yasue
Author_Institution :
Dept. of Syst. Design Eng., Keio Univ., Yokohama, Japan
fDate :
Oct. 29 2013-Nov. 1 2013
Abstract :
In this paper, we propose a sound quality evaluation system using electroencephalogram (EEG) and group method of data handling (GMDH) type neural network. Recently, EEG is used in various applications, and we focus on sound quality evaluation using EEG. We prepared EEG samples to train a GMDH-type neural network to recognise 3 typical types of sound which was used to create the training data. The results showed that using GMDH-type neural network improved recognition rate compared to the other method. Additionally, we repeated simulations by using different parameter of GMDH-type neural network, and the open test results showed the recognition rate variations in different parameter values.
Keywords :
data handling; electroencephalography; medical signal processing; neural nets; EEG-type neural network; GMDH-type neural network; electroencephalogram; group method of data handling; recognition rate; recognition rate variations; sound quality evaluation; sound quality evaluation system; sound quality indicating system; Biological neural networks; Electroencephalography; Feature extraction; Loudspeakers; Neurons; Principal component analysis;
Conference_Titel :
Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific
Conference_Location :
Kaohsiung
DOI :
10.1109/APSIPA.2013.6694124