| Project/Area Number |
16500140
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Tokyo Denki University |
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Principal Investigator |
KASHIWAZAKI Naoya Tokyo Denki University, School of Science and Engineering, Associate Professor, 理工学部, 助教授 (60204385)
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| Co-Investigator(Kenkyū-buntansha) |
SHIBATA Ryoji Tokyo Denki University, School of Science and Engineering, Associate Professor, 理工学部, 助教授 (20328529)
SHIBAYAMA Takuro Tokyo Denki University, School of Science and Engineering, Instructor, 理工学部, 助手 (80366385)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 2006: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2005: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2004: ¥800,000 (Direct Cost: ¥800,000)
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| Keywords | Kansei Engineering / Kansei Parameter / Kansei Informations / 感性情報 / 感性パラメータ法 |
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| Research Abstract |
Kansei Parameter method is developed for making standard values of Kansei informations to applied for engineering. In this research, we have investigated about hearing and taste of fragrance.
Music downloaded from server is classified into some "Genres" by some categories such as artist, domains and associations. However taste and feeling of music sometimes varies even in the same artist's tune, music has almost been classified by artist name. It is good for searching music in the internet that music is classified by music feelings or listener's "Kansei".
A method of classification of music by Kansei is described in this thesis. Music were classified some gorups using Kansei-parameter method and its factor analysis. This result corresponded with the feeling or Kansei which a listener thought of well. It is considered that genre-classification using Kansei-parameter is a meaningful method at the point of that the user can get the music he wants.
Many goods of fragrance are sold. It is difficult to explain in language such fragrance because of their intricately. In this research, the feature of fragrance is explained in values using Kansei parameter method. Value are calcurated from figures and colors that subjects choose. The experiment was conducted for the office worker and the college student by making 15 kinds of perfumes into a sample. Evaluation by SD method was also conducted as comparison. The result of Kansei parameter method was not same as classification of a fragrance. From comparison with SD method, it was shown that it can make classify from a new point of view, according to Kansei parameter. The results from office workers and college students includes many different characteristics. It is thought that age etc. has influenced to choose fragrance. Finally the data for every sample was transposed to Kansei parameter object. It became that out of which the feature of each sample came.
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