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Predicting the colour associated with odours using an electronic nose

Ward, R, Rahman, S, Wuerger, S and Marshall, A (2021) Predicting the colour associated with odours using an electronic nose. In: Proceedings of the 1st Workshop on Multisensory Experiences - SensoryX'21 . (ACM International Conference on Interactive Media Experience, June 21-23, 2021, NY, USA).

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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 or Workshop Item (Paper)
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > Q Science (General)
Q Science > QA Mathematics
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Computer Science & Mathematics
Publisher: Brazilian Computing Society
SWORD Depositor: A Symplectic
Date Deposited: 06 Jun 2023 12:00
Last Modified: 06 Jun 2023 12:00
DOI or ID number: 10.5753/sensoryx.2021.15683
URI: https://researchonline.ljmu.ac.uk/id/eprint/19618
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