Asians’ Facial Responsiveness to Basic Tastes by Automated Facial Expression Analysis System

Growing evidence shows that consumer choices in real life are mostly driven by unconscious mechanisms rather than conscious. The unconscious process could be measured by behavioral measurements. This study aims to apply automatic facial expression analysis technique for consumers’ emotion representation, and explore the relationships between sensory perception and facial responses. Basic taste solutions (sourness, sweetness, bitterness, umami, and saltiness) with 6 levels plus water were used, which could cover most of the tastes found in food and drink. The other contribution of this study is to analyze the characteristics of facial expressions and correlation between facial expressions and perceptive hedonic liking for Asian consumers. Up until now, the facial expression application researches only reported for western consumers, while few related researches investigated the facial responses during food consuming for Asian consumers. Experimental results indicated that facial expressions could identify different stimuli with various concentrations and different hedonic levels. The perceived liking increased at lower concentrations and decreased at higher concentrations, while samples with medium concentrations were perceived as the most pleasant except sweetness and bitterness. High correlations were founded between perceived intensities of bitterness, umami, saltiness, and facial reactions of disgust and fear. Facial expression disgust and anger could characterize emotion “dislike,” and happiness could characterize emotion “like,” while neutral could represent “neither like nor dislike.” The identified facial expressions agree with the perceived sensory emotions elicited by basic taste solutions. The correlation analysis between hedonic levels and facial expression intensities obtained in this study are in accordance with that discussed for western consumers. Practical Application Facial expression analysis is one of the most important methods of indicating true emotions of consumers. Automatic facial expression analysis could help knowing the preferences of consumers directly and guide for the product development and improvement.