A Study of Odor Reproduction Using Odor Components Based on Human Perception Data

カテゴリ: 研究会(論文単位)

論文No: CHS24016

グループ名: 【E】センサ・マイクロマシン部門 ケミカルセンサ研究会

発行日: 2024/07/01

タイトル(英語): A Study of Odor Reproduction Using Odor Components Based on Human Perception Data

著者名: Hu Jingcheng(東京工業大学),Aleixandre Manuel(東京工業大学),Prasetyawan Dani (東京工業大学),中本 高道(東京工業大学)

著者名(英語): Jingcheng Hu(Tokyo Institute of Technology),Manuel Aleixandre(Tokyo Institute of Technology),Dani Prasetyawan(Tokyo Institute of Technology),Takamichi Nakamoto(Tokyo Institute of Technology)

キーワード: Odor character|Machine learning|Mass spectrum|Dimensionality reduction

要約(日本語): Auditory and visual information has been widely studied, whereas we learned little about olfaction. In this study, we proposed a model to predict human olfactory perception data using mass spectrum data of essential oils. Furthermore, a better result was generalized through the introduction of natural language processing technique. At the end of the study, we discussed one possible way to achieve odor reproduction using the proposed model.

要約(英語): Auditory and visual information has been widely studied, whereas we learned little about olfaction. In this study, we proposed a model to predict human olfactory perception data using mass spectrum data of essential oils. Furthermore, a better result was generalized through the introduction of natural language processing technique. At the end of the study, we discussed one possible way to achieve odor reproduction using the proposed model.

本誌: 2024年7月4日-2024年7月5日ケミカルセンサ研究会

本誌掲載ページ: 13-16 p

原稿種別: 英語

PDFファイルサイズ: 1,187 Kバイト