Home // International Journal On Advances in Intelligent Systems, volume 17, numbers 1 and 2, 2024 // View article
Authors:
Katsuko Nakahira, T.
Munenori Harada
Shunsuke Moriya
Muneo Kitajima
Keywords: Local-Global Reaction Map; Pupil Response; Affective Norm for English Words; Emotion Induction; Contents Design of Auditory Information.
Abstract:
When a person acquires a text as auditory information and derives the meaning of the text, he or she may simultaneously generate an emotion in response to the content of the text. Emotions are said to have a certain relationship with decision-making and memory. Therefore, it is expected that even sentences with the same meaning will be remembered differently depending on the emotion evoked. This study aims to clarify the relationship between the emotions that arise when listening to a text and the memory of the presented text. The classification of emotional states held by people is performed by a method based on subjective quantities by impression rating or by a method based on objective quantities by biometric information. In this study, we focus on pupil response, which is biological information that has been suggested to change with emotion. Based on this, this paper proposes the Local-Global Reaction Map (LGR-Map) as a classification method for pupil changes accompanying emotional changes, as a basic research for the construction of adaptive content design methods that utilize the degree of human emotional arousal. The LGR-Map is generated by capturing the emotional changes during listening to a text from the following two perspectives; Those generated by words in a specific region of a sentence (Local reaction); those generated by the context of the entire sentence (Global reaction). The total pupil diameter change within a certain time period is obtained as the characteristic quantity for each response. Error ellipses are defined for the distribution of listeners in the LR-GR for the presented text (LGR-Map), and classified into five types based on the rotation angle and flattening ratio of the error ellipses. The basic properties of the LGR-Map were investigated by using auditory stimuli presented in short sentences containing Affective Norm for English Words (ANEW). As an extension, we will attempt to create an extended LGR-Map for sentences with multiple ANEWs and consider whether it is possible to extract features of the pupillary response. In addition, we discuss the consistency of the results of a recall test in relation to the cognitive model.
Pages: 38 to 48
Copyright: Copyright (c) to authors, 2024. Used with permission.
Publication date: June 30, 2024
Published in: journal
ISSN: 1942-2679