- Japan Society of Kansei Engineering
- 日本感性工学会論文誌 (ISSN:18840833)
This paper describes linguistic features of generally unreadable person names, which are defined as "<I>KIRAKIRA</I> names," and proposes a method to detect <I>KIRAKIRA</I> names based on the features. Through the discussions, the following eight features are founded as the linguistic features of <I>KIRAKIRA</I> names: 1) Too many Kanji characters, 2) Too many syllables, 3) Multiple usage of a common Kanji character, 4) Kanji variants are used, 5) The pronunciation of Kanji is generally unknown, 6) Too many stroke count for Kanji, 7) Mismatching of gender between a person and the name, and 8) The pronunciation of name equals an imported word. Based on the features, <I>KIRAKIRA</I> names are automatically detected by using Support Vector Machine. The experiments to detect <I>KIRAKIRA</I> names were conducted for 10,000 names. The results of the experiments showed 81.79% accuracy, 76.89% precision, and 91.84% recall.