Speech-based recognition of self-reported and observed emotion in a dimensional space

The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two types of ratings affect the development and performance of automatic emotion recognizers developed with these ratings. A dimensional approach to emotion modeling is adopted: the ratings are based on continuous arousal and valence scales. We describe the TNO-Gaming Corpus that contains spontaneous vocal and facial expressions elicited via a multiplayer videogame and that includes emotion annotations obtained via self-report and observation by outside observers. Comparisons show that there are discrepancies between self-reported and observed emotion ratings which are also reflected in the performance of the emotion recognizers developed. Using Support Vector Regression in combination with acoustic and textual features, recognizers of arousal and valence are developed that can predict points in a 2-dimensional arousal-valence space. The results of these recognizers show that the self-reported emotion is much harder to recognize than the observed emotion, and that averaging ratings from multiple observers improves performance

Performance of grassed swale as stormwater quantity control in lowland area

Grassed swale is a vegetated open channel designed to attenuate stormwater through infiltration and conveying runoff into nearby water bodies, thus reduces peak flows and minimizes the causes of flood. UTHM is a flood-prone area due to located in lowland area, has high groundwater level and low infiltration rates. The aim of this study is to assess the performance of grassed swale as a stormwater quantity control in UTHM. Flow depths and velocities of swales were measured according to Six-Tenths Depth Method shortly after a rainfall event. Flow discharges of swales (Qswale) were evaluated by Mean- Section Method to determine the variations of Manning’s roughness coefficients (ncalculate) that results between 0.075 – 0.122 due to tall grass and irregularity of channels. Based on the values of Qswale between sections of swales, the percentages of flow attenuation are up to 54%. As for the flow conveyance of swales, Qswale were determined by Manning’s equation that divided into Qcalculate, evaluated using ncalculate, and Qdesign, evaluated using roughness coefficient recommended by MSMA (ndesign), to compare with flow discharges of drainage areas (Qpeak), evaluated by Rational Method with 10-year ARI. Each site of study has shown Qdesign is greater than Qpeak up to 59%. However, Qcalculate is greater than Qpeak only at a certain site of study up to 14%. The values of Qdesign also greater than Qcalculate up to 52% where it shows that the roughness coefficients as considered in MSMA are providing a better performance of swale. This study also found that the characteristics of the studied swales are comparable to the design consideration by MSMA. Based on these findings, grassed swale has the potential in collecting, attenuating, and conveying stormwater, which suitable to be applied as one of the best management practices in preventing flash flood at UTHM campus

Plug-in to fear: game biosensors and negative physiological responses to music

The games industry is beginning to embark on an ambitious journey into the world of biometric gaming in search of more exciting and immersive gaming experiences. Whether or not biometric game technologies hold the key to unlock the “ultimate gaming experience” hinges not only on technological advancements alone but also on the game industry’s understanding of physiological responses to stimuli of different kinds, and its ability to interpret physiological data in terms of indicative meaning. With reference to horror genre games and music in particular, this article reviews some of the scientific literature relating to specific physiological responses induced by “fearful” or “unpleasant” musical stimuli, and considers some of the challenges facing the games industry in its quest for the ultimate “plugged-in” experience

Internet gaming disorder as a formative construct : implications for conceptualization and measurement

Background. Some people have serious problems controlling their internet and video game use. The DSM-5 now includes a proposal for ‘Internet Gaming Disorder’ as a condition in need of further study. Various studies aim to validate the proposed diagnostic criteria for Internet Gaming Disorder and multiple new scales have been introduced that cover the suggested criteria. Approach. Using a structured approach, we demonstrate that Internet Gaming Disorder might be better interpreted as a formative construct, as opposed to the current practice of conceptualizing it as a reflective construct. Incorrectly approaching a formative construct as a reflective one causes serious problems in scale development including (a) incorrect reliance on item-to-total scale correlation to exclude items and incorrectly relying on indices of inter-item reliability that do not fit the measurement model (e.g., Cronbach’s α) (b) incorrect interpretation of composite or mean scores that assume all items are equal in contributing value to a sum score, and (c) biased estimation of model parameters in statistical models. Implications. We show that these issues are impacting current validation efforts through two recent examples. A reinterpretation of Internet Gaming Disorder as a formative construct has broad consequences for current validation efforts and provides opportunities to reanalyze existing data. We discuss three broad implications for current research: (1) Composite latent constructs should be defined and used in models, (2) Item exclusion and selection should not rely on item-to-total scale correlations, and (3) Existing definitions of Internet Gaming Disorder should be enriched further

A longitudinal study for the empirical validation of an etiopathogenetic model of internet addiction in adolescence based on early emotion regulation

Several etiopathogenetic models have been conceptualized for the onset of Internet Addiction (IA). However, no study had evaluated the possible predictive efect of early emotion regulation strategies on the development of IA in adolescence. In a sample of N = 142 adolescents with Internet Addiction, this twelve-year longitudinal study aimed at verifying whether and how emotion regulation strategies (self-focused versus other-focused) at two years of age were predictive of school-age children's internalizing/externalizing symptoms, which in turn fostered Internet Addiction (compulsive use of the Web versus distressed use) in adolescence. Our results confrmed our hypotheses demonstrating that early emotion regulation has an impact on the emotional-behavioral functioning in middle childhood (8 years of age), which in turn has an infuence on the onset of IA in adolescence. Moreover, our results showed a strong, direct statistical link between the characteristics of emotion regulation strategies in infancy and IA in adolescence. Tese results indicate that a common root of unbalanced emotion regulation could lead to two diferent manifestations of Internet Addiction in youths and could be useful in the assessment and treatment of adolescents with I

A longitudinal study for the empirical validation of an etiopathogenetic model of internet addiction in adolescence based on early emotion regulation

Several etiopathogenetic models have been conceptualized for the onset of Internet Addiction (IA). However, no study had evaluated the possible predictive efect of early emotion regulation strategies on the development of IA in adolescence. In a sample of N = 142 adolescents with Internet Addiction, this twelve-year longitudinal study aimed at verifying whether and how emotion regulation strategies (self-focused versus other-focused) at two years of age were predictive of school-age children's internalizing/externalizing symptoms, which in turn fostered Internet Addiction (compulsive use of the Web versus distressed use) in adolescence. Our results confrmed our hypotheses demonstrating that early emotion regulation has an impact on the emotional-behavioral functioning in middle childhood (8 years of age), which in turn has an infuence on the onset of IA in adolescence. Moreover, our results showed a strong, direct statistical link between the characteristics of emotion regulation strategies in infancy and IA in adolescence. Tese results indicate that a common root of unbalanced emotion regulation could lead to two diferent manifestations of Internet Addiction in youths and could be useful in the assessment and treatment of adolescents with I

A Palette of Deepened Emotions: Exploring Emotional Challenge in Virtual Reality Games

Recent work introduced the notion of ‘emotional challenge’promising for understanding more unique and diverse player experiences (PX). Although emotional challenge has immediately attracted HCI researchers’ attention, the concept has not been experimentally explored, especially in virtual reality (VR), one of the latest gaming environments. We conducted two experiments to investigate how emotional challenge affects PX when separately from or jointly with conventional challenge in VR and PC conditions. We found that relatively exclusive emotional challenge induced a wider range of different emotions in both conditions, while the adding of emotional challenge broadened emotional responses only in VR. In both experiments, VR significantly enhanced the measured PX of emotional responses, appreciation, immersion and presence. Our findings indicate that VR may be an ideal medium to present emotional challenge and also extend the understanding of emotional (and conventional) challenge in video games

Why do gamers buy 'virtual assets'? An insight in to the psychology behind purchase behaviour

The present study investigated the phenomenon of buying 'virtual assets' for game avatars. Virtual Assets are items that are bought with real-world money for an avatar in-game. Weapons, items, pets, mounts and skin customisations are the most popular examples. Using a qualitative methodology - in this case Interpretative phenomenological analysis (IPA) - six gamers that regularly bought in - game assets were interviewed. IPA was chosen because of its emphasis on lived experience, and each participant had subjective experiences of gaming and purchase behaviour. Of particular focus in this study were the superordinate themes of motivations for purchase behaviour, the resulting psychological impact on the gamer, the social benefits of gaming and virtual asset purchasing, emotional attachment, self-expression through the avatar, impulsivity versus thoughtfulness in purchase intention, and the impact of a transaction machinery on the 'game experience'. Motivations that were found to be of particular importance were item exclusivity, function, social appeal, and collectability. It was found that virtual items enable the gamer to express themselves, feel real satisfaction, and build lasting friendships. Essentially, virtual assets and gaming mostly had a very positive impact on the participant’s psychological wellbeing. Implications for gamers and games production companies are considered

Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data

Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating comprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor). An approach build on discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. In order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Such mechanism can yield a platform for objective and effortless assessment of human activity within the context of serious gaming and human-computer interaction.Comment: 8th Computer Science and Electronic Engineering, (CEEC 2016), University of Essex, UK, 6 page