Predicting the colour associated with odours using an electronic nose

Ward, Ryan, Rahman, Shammi, Wuerger, Sophie and Marshall, Alan ORCID: 0000-0002-8058-5242 (2021) Predicting the colour associated with odours using an electronic nose In: Proceedigs of the 1st Workshop on Multisensory Experiences (SensoryX 2021).

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Abstract

Predicting olfactory perception with an electronic nose can aid in the design and evaluation of olfactory-based experiences. We investigate whether the human perception of odours can be predicted outside the bounds of perceived pleasantness and semantic descriptors. We tuned an electronic nose to predict an odour's colour in the CIELAB colour space using human judgements. This revealed that the crossmodal associations people have towards colours could be predicted. Our electronic nose system can predict an odour's colour with a 70 – 81% machine-human similarity rating. These findings suggest a systematic and predictable link exists between the chemical features of odours and the colour associated to them. These findings highlight the possibilities of predicting human olfactory perception using an electronic nose.

Item Type:	Conference Item (Unspecified)
Uncontrolled Keywords:	5202 Biological Psychology, 46 Information and Computing Sciences, 52 Psychology, Clinical Research
Divisions:	Faculty of Science & Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	25 Aug 2021 11:20
Last Modified:	23 May 2026 06:14
DOI:	10.5753/sensoryx.2021.15683
Related Websites:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3134699
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