Sound quality indicating system using EEG and GMDH-type neural network

Kiminobu Nishimura, Yasue Mitsukura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publication2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 - Kaohsiung, Taiwan, Province of China
Duration: 2013 Oct 292013 Nov 1

Publication series

Name2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013

Other

Other2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
CountryTaiwan, Province of China
CityKaohsiung
Period13/10/2913/11/1

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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  • Cite this

    Nishimura, K., & Mitsukura, Y. (2013). Sound quality indicating system using EEG and GMDH-type neural network. In 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 [6694124] (2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013). https://doi.org/10.1109/APSIPA.2013.6694124