Abstract
This chapter describes the trends in the phonemes used in naming by using the attributes of objects. The study used the names of characters in video games and automobiles as the targets of analysis. By categorizing the objects based on their attributes, the study sought to verify if there existed a difference in the used phonemes between the categories. As a result, the study clarified the phonemes used to illustrate smallness, lightness, and weakness in addition to the phonemes used to depict largeness, heaviness, and strength between two objects. In addition, the study also employed evaluation experiments to verify the trends in the phonemes used in naming, which was derived from the analyses of the objects’ attributes, and to verify whether the phonemes used in the naming process matched people’s impressions. Through this process, the study identified the objects’ specific naming trends and the characteristics of the phonemes. By performing the same analysis process for many objects, the study hopes to propose a supporting method for the naming process of specific objects.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Iida A (2012) Naming says things. Chuo University Press
Kurokawa I (2012) Sensitive naming lab. People decide what is “good or bad” by their language sense. Kawade Shobo Shinsha
Kidori T (2004) The essence of naming: the charm of Japanese is the creation of sound. Chikuma Shobo
Kidori T (1990) Sound. President Co.
Yorkston E, Menon G (2004) A sound idea: phonetic effects of brand names on consumer judgments. J Consumer Res. https://doi.org/10.1086/383422
Klink RR (2000) Creating brand names with meaning: the use of sound symbolism. Market Lett. https://doi.org/10.1023/A:1008184423824
Klink RR (2001) Creating meaningful new brand names: a study of semantics and sound symbolism. J Market Theor Prac. https://doi.org/10.1080/10696679.2001.11501889
Klink RR (2003) Creating meaningful brands: the relationship between brand name and brand mark. Market Lett. https://doi.org/10.1023/A:1027476132607
Jaewoo P, Ose Y (2009) Effects of pronunciation of brand name on brand evaluation: approach from sound symbolism, consumer behavior research. https://doi.org/10.11194/acs.16.1_23
Jaewoo P (2010) Basic analysis of product attribute associations by brand name pronunciation. Economics 245:80–99
Nagamachi M (1993) Kansei engineering on sound of words. Jpn J Acoust Soc. https://doi.org/10.20697/jasj.49.9_638
Nagamachi M, Matsubara Y, Maeda H, Ohgama T (2018) Brand name decision AI system. In: Proceedings of the 7th international conference on Kansei engineering and emotion research. https://doi.org/10.1007/978-981-10-8612-0_5
Doizaki R, Shimizu Y, Sakamoto M (2012) Image evaluation system based on the sound symbolism of brand names. In: IEEE soft computing and intelligent systems (SCIS) and 13th international symposium on advanced intelligent systems (ISIS). https://doi.org/10.1109/scis-isis.2012.6505236
Namer 7Lite. http://www.bds.ne.jp. Accessed 26 Apr 2019
Shimizu Y, Dobasaki R, Sakamoto M (2014) A system for estimating a detailed impression of individual onomatopoeia. J Jpn Soc Artif Intell. https://doi.org/10.1527/tjsai.29.41
Fujisawa N, Obata F, Takada M, Iwamiya S (2006) Impression of sound imaged from onomatopoeia of 2 mora. J Acoust Soc Jpn. https://doi.org/10.20697/jasj.62.11_774
Nakabe F, Watanabe C (2009) Development of onomatopoeia learning system using Kansei information. 1st Forum Papers on Data Engineering and Information Management
Miura S, Murata M, Yasuda S, Miyabe M, Aramaki E (2012) Reproduction of phonetic symbols by machine learning: creation of the strongest Pokemon. The Association of Language Processing
Kawahara S, Noto A, Kumagai G (2018) Sound symbolic patterns in Pokémon names. Phonetica. https://doi.org/10.1159/000484938
Daijirin, Japanese sounds, 3rd edn. http://daijirin.dual-d.net/extra/nihongoon.html. Sanseido. Accessed 26 Apr 2019
Matsubara N, Nada K, Nakai K (1991) Introduction to statistics. The University of Tokyo Press
Crawley MJ, Nomaguchi K, Kikuchi Y (2016) Statistics: introduction using R, 2nd revision. Kyoritsu Publishing Co. Ltd.
Miyagawa M, Aok S (2018) Statistical library, statistical analysis of contingency tables—from 2D to multi-dimensional. Asakura Shoten
Official Pokemon Picture Book. http://www.pokemon.jp/zukan. Accessed 26 Apr 2019
Kurokawa I (2004) Why the name of the monster is Gagigugego. Shinchosha
Iwanaga Y (2002) This will really sell! Naming success law. PHP Institute
Car sensor. https://www.automobilesensor.net/. Recruit Marketing Partners Inc. Accessed 26 Apr 2019
Goonet. https://www.goo-net.com/. Proto Corporation. Accessed 26 Apr 2019
Kazuko S, Kawahara S (2013) The sound symbolic nature of Japanese maid names. In: Proceedings of the 13th annual meeting of the Japanese cognitive linguistics association
Iwanaga Y (1990) Naming to sell. Naming to buy. Dobunkan, pp 200–204
Ohala J (1984) An ethological perspective on common cross-language utilization of FO of voice. Phonetica. https://doi.org/10.1159/000261706
Jaewoo P, Ose Y (2019) Effects of brand name pronunciation on product attribute association and brand attitude. Nikkei Advertising Institute
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Hamada, Y., Shoji, H. (2020). The Relationship Between Attributes of Objects and Phonemes of Naming. In: Fukuda, S. (eds) Emotional Engineering, Vol. 8. Springer, Cham. https://doi.org/10.1007/978-3-030-38360-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-38360-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-38359-6
Online ISBN: 978-3-030-38360-2
eBook Packages: EngineeringEngineering (R0)