| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| AIT, IIEEJ, AS, CG-ARTS |
2024-03-05
10:55 |
Tokyo |
Tokyo University of Technology (Tokyo) |
Building a Music Creation System for a One Time Experience
Akihiro Suzuki, Kenichiro ITO (TUT) |
The objective of this research is to create “one-time music” using chance, through space and time interwoven between peo... [more] |
AIT2024-59
pp.93-96 |
| ME |
2021-02-27
10:30 |
|
|
Relation between Sound Frequencies and Human Emotional Characteristics
Mituski Ootani, Yasuyuki Saito (NITKC) |
In this study, we investigate the relationship between the timbre of a musical instrument and human emotions
with respe... [more] |
ME2021-33
pp.17-20 |
| AIT, IIEEJ, AS, CG-ARTS |
2020-03-13
11:20 |
Tokyo |
Tokyo University of Technology (Tokyo)
(Cancelled) |
An Assessment of Feet Sensitivity for Musical Signal Vibration
-- Through Development of "foovi" as a Sound Media Transducer --
Yukiua Endo, Akinori Ito (TUT) |
In this study, we developed a music viewing device that uses the vibration sensation on the human foot as an extension o... [more] |
AIT2020-103
pp.181-184 |
| AIT, IIEEJ, AS, CG-ARTS |
2019-03-12
14:00 |
Tokyo |
Waseda Univ. (Tokyo) |
A Music Recommendation System Considering the Location-based Ordinariness
Narumi Kuroko (Ocha Univ.), Hayato Oya (RecoChoku), Takayuki Itoh (Ocha Univ.) |
The mainstream of the music media purchase has moved from discs such as CDs to distribution via the Internet. Also, the ... [more] |
AIT2019-146
pp.341-344 |
| AIT, IIEEJ, AS, CG-ARTS |
2019-03-12
14:00 |
Tokyo |
Waseda Univ. (Tokyo) |
Analysis of auditory characteristics of distorted music
Yuma Ono, Keiko Ochi, Yasunari Obuchi (Tokyo Univ. Tech.) |
Recent commercial trends for high sound pressure music brought about the modification of music so as to increase the sou... [more] |
AIT2019-147
pp.345-346 |
| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-15
15:45 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
A Note on Estimation of Users' Emotion Evoked During Listening to Music
-- Performance Improvement Based on Deep Learning Method --
Hakusyou Dan, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a method that estimates users’ emotion evoked during listening to music. In our method, we use audio... [more] |
MMS2018-21 HI2018-21 ME2018-21 AIT2018-21
pp.201-206 |
| CE, MMS, AIT, HI, ME, IEICE-ITS, IEICE-IE [detail] |
2017-02-20
15:30 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
A note on estimation of users' emotion evoked during listening to music
-- Performance improvement base on fusion of multiple estimation results --
Boxiao Duan, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper precent estimation of users' emotion evoked during listening to music. In our method, we focus on RUSBagging ... [more] |
MMS2017-44 CE2017-44 HI2017-44 ME2017-68 AIT2017-44
pp.349-354 |
| HI, IEICE-IE, AIT, IEICE-ITS, ME, MMS [detail] |
2015-02-23
11:00 |
Hokkaido |
Hokudai (Hokkaido) |
A Note on Classification of Individual Favorite Musical Pieces Utilizing EEG Signals during Listening to Music
-- Performance Improvement via CCA Considering Class Information --
Ryosuke Sawata, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a new method using individual EEG signals for improving his/her favorite music classification. Our p... [more] |
MMS2015-21 CE2015-21 HI2015-19 ME2015-19 AIT2015-19
pp.179-184 |