• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.217-218
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• 2009

총 19 명 (male=9, female=10)을 대상으로 자기 보고식 질문지를 일주일 간격으로 2 회 수행한 후 double blind 방식과 실험 목적/프로토콜을 피검자에게 알려주지 않은 상태로 EEG 검사를 수행하여 행동활성화체계/행동억제체계(BAS/BIS)를 분석하였다. 안정기를 거친 후 갑자기 불유쾌한 청각적 자극(1Hz, 110dB, 15초간)을 2 회 실시하여 BAS/BIS 수치의 변화를 분석하였다. 분노활성화 음성자극에 대한 BAS/BIS 성향 대상자들의 반응을 분석하여 그 변화추이를 살펴보고자 함이 본 연구의 목적이다.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.406-416
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• 2023

Alarm system performance is a critical aspect of safety. While existing research has extensively examined the influence of acoustic attributes on alarm performance, consonance's impact remains largely uncharted territory. This study bridges this research gap by investigating the effect of consonance on alarm systems. We extend our investigation to encompass not only the sound characteristics of the alarm but also the acoustic qualities of the surrounding environment, recognizing their potential impact on alarm efficacy. Prior studies consistently link consonance to annoyance levels, resulting in a negative user experience. Thus, we explore the relationship between consonance and alarm system performance, with a particular focus on modulating annoyance as an explanatory factor. Utilizing an oddball paradigm, we categorized standard and oddball sounds into consonant and dissonant types, creating four sound combinations. Participants were asked to respond to the irregularly presented oddball sounds while ignoring the constantly presented standard sounds. Our results reveal significant differences between groups, with the Standard Consonant/Oddball Dissonant (SC/OD) group displaying notably slower response times than the Standard Dissonant/Oddball Consonant (SD/OC) group. This reaction time variation aligns with differences in annoyance levels, as the SC/OD group reports higher annoyance, suggesting that reaction time discrepancies may be linked to increased arousal due to heightened annoyance.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.117-124
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• 2013

This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.