Presentation | 2017-03-01 [Poster Presentation] Estimation of Music Genres from Spontaneous Brain Activity Analysis by Using Neural Network Hiroki Itoga, Yoshikazu Washizawa, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Quantitative evaluation of the mind states has been addressed for a long time. Evaluated mind states can be applied for many applications. For example, recommendation technology such as music is researched widely. Some of them utilized EEG for emotional states estimation. In this study, music genres estimated by EEG and features were effective for genre estimation are studied. In 5 class genre recognition, we achieved 38.1±9.4% recog- nition accuracy, it is higher than chance level, 20%. The features that are effective for genre estimation differs for each subject, however the result showed an association with emotional states. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | EEG / Spontaneous brain activity analysis / Neural Networks / Genre recognition / Feature Extraction |
Paper # | EA2016-103,SIP2016-158,SP2016-98 |
Date of Issue | 2017-02-22 (EA, SIP, SP) |
Conference Information | |
Committee | SP / SIP / EA |
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Conference Date | 2017/3/1(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Okinawa Industry Support Center |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics |
Chair | Kazunori Mano(Shibaura Inst. of Tech.) / Makoto Nakashizuka(Chiba Inst. of Tech.) / Mitsunori Mizumachi(Kyushu Inst. of Tech.) |
Vice Chair | Hiroki Mori(Utsunomiya Univ.) / Masahiro Okuda(Univ. of Kitakyushu) / Shogo Muramatsu(Niigata Univ.) / Yoichi Haneda(Univ. of Electro-Comm.) / Suehiro Shimauchi(NTT) |
Secretary | Hiroki Mori(Kobe Univ.) / Masahiro Okuda(Shizuoka Univ.) / Shogo Muramatsu(Ritsumeikan Univ.) / Yoichi Haneda(Chiba Inst. of Tech.) / Suehiro Shimauchi(KDDI R&D Labs.) |
Assistant | Taichi Asami(NTT) / Kei Hashimoto(Nagoya Inst. of Tech.) / Osamu Watanabe(Takushoku Univ.) / Shigeto Takeoka(Shizuoka Inst. of Science and Tech.) / TREVINO Jorge(Tohoku Univ.) |
Paper Information | |
Registration To | Technical Committee on Speech / Technical Committee on Signal Processing / Technical Committee on Engineering Acoustics |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | [Poster Presentation] Estimation of Music Genres from Spontaneous Brain Activity Analysis by Using Neural Network |
Sub Title (in English) | |
Keyword(1) | EEG |
Keyword(2) | Spontaneous brain activity analysis |
Keyword(3) | Neural Networks |
Keyword(4) | Genre recognition |
Keyword(5) | Feature Extraction |
1st Author's Name | Hiroki Itoga |
1st Author's Affiliation | The University of Electro-Communications(UEC) |
2nd Author's Name | Yoshikazu Washizawa |
2nd Author's Affiliation | The University of Electro-Communications(UEC) |
Date | 2017-03-01 |
Paper # | EA2016-103,SIP2016-158,SP2016-98 |
Volume (vol) | vol.116 |
Number (no) | EA-475,SIP-476,SP-477 |
Page | pp.pp.119-122(EA), pp.119-122(SIP), pp.119-122(SP), |
#Pages | 4 |
Date of Issue | 2017-02-22 (EA, SIP, SP) |