Recognizing induced emotions of movie audiences: Are induced and perceived emotions the same?

Abstract

Abstract-Predicting the emotional response of movie audiences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience's perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and induced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and behavioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction.

Recognizing Induced Emotions of Movie Audiences from Multimodal Information

“…We describe below collection of the extended annotations [19] of the C. LIRIS-ACCEDE database with their detailed statistics. These include transcripts of movie dialogues with word timings and affective cue labels in Section 3.3, perceived emotion annotations in Section 3.4, and an analysis of agreement on perceived and induced emotion annotations in Section 3.5.…”

“…Besides investigating discriminative power of multimodal features, we studied the impact of including temporal information on the recognition performance as well as different fusion strategies for combining multimodal information (i.e., audio, visual, lexical movie content, perceived emotion and aesthetic highlight annotations as well as spectators' physiological and behavioral reactions). This paper is the extension of our previous work [19], addressing the following research questions:…”

Enabling Responsible Online Gambling by Real-time Persuasive Technologies

“…From an affective computing point of view, attempting to capture gambling emotions results in several open issues that need to be investigated, such as the synchronous capture of physiological and behavioural signals and the identification of the most important modalities for emotion detection while gambling [41], [42], [43], [48]. Moreover, we need to identify how the different modalities correlate during an experience, e.g.…”

Empowering responsible online gambling by real-time persuasive information systems

“…A combination of different multimodal measures, such as facial expressions and galvanic skin response, can help us better understand the role of emotions in gambling. From an affective computing point of view, attempting to capture gambling emotions results in several open issues that need to be investigated, such as the synchronous capture of physiological and behavioural signals and the identification of the most important modalities for emotion detection while gambling [26], [27], [28], [29]. Moreover, we need to identify how the different modalities correlate during an experience, e.g., the correlation between galvanic skin response and facial expressions (intrapersonal correlations) [30].…”