Cross-Cultural Patterns in Dynamic Ratings of Positive and Negative Natural Emotional Behaviour

Background: Studies of cross-cultural variations in the perception of emotion have typically compared rates of recognition of static posed stimulus photographs. That research has provided evidence for universality in the recognition of a range of emotions but also for some systematic cross-cultural variation in the interpretation of emotional expression. However, questions remain about how widely such findings can be generalised to real life emotional situations. The present study provides the first evidence that the previously reported interplay between universal and cultural influences extends to ratings of natural, dynamic emotional stimuli.

Methodology/Principal Findings: Participants from Northern Ireland, Serbia, Guatemala and Peru used a computer based tool to continuously rate the strength of positive and negative emotion being displayed in twelve short video sequences by people from the United Kingdom engaged in emotional conversations. Generalized additive mixed models were developed to assess the differences in perception of emotion between countries and sexes. Our results indicate that the temporal pattern of ratings is similar across cultures for a range of emotions and social contexts. However, there are systematic differences in intensity ratings between the countries, with participants from Northern Ireland making the most extreme ratings in the majority of the clips.

Conclusions/Significance: The results indicate that there is strong agreement across cultures in the valence and patterns of ratings of natural emotional situations but that participants from different cultures show systematic variation in the intensity with which they rate emotion. Results are discussed in terms of both ‘in-group advantage’ and ‘display rules’ approaches. This study indicates that examples of natural spontaneous emotional behaviour can be used to study cross-cultural variations in the perception of emotion.

Gender differences in the role of emotional intelligence during the primary-secondary school transition

The relationship between components of emotional intelligence (EI) (interpersonal
ability, intrapersonal ability, adaptability and stress management) and academic
performance in English, maths and science was examined in a sample of 86 children
(49 males and 37 females) aged 11–12 years during the primary–secondary school
transition period. Results indicated that for both males and females, intrapersonal
ability had little relationship with academic achievement, while adaptability had the
strongest relationship with achievement in all subjects. Gender differences were particularly
pronounced for science, for which stronger relationships were observed with all
EI components for males. In addition, apparent only for males was a negative
relationship between stress management and science. These findings offer support for
the current inclusion of a personal and emotional element in the primary school curriculum,
and indicate that such training is likely to help males more than females to make
a successful transition from primary to secondary school.

Emotional intelligence, personality and decoding non-verbal expressions of emotion

Previous research has highlighted theoretical and empirical links between measures of both personality and trait emotional intelligence (EI), and the ability to decode facial expressions of emotion. Research has also found that the posed, static characteristics of the photographic stimuli used to explore these links affects the decoding process and differentiates them from the natural expressions they represent. This undermines the ecological validity of established trait-emotion decoding relationships. This study addresses these methodological shortcomings by testing relationships between the reliability of participant ratings of dynamic, spontaneously elicited expressions of emotion with personality and trait EI. Fifty participants completed personality and self-report EI questionnaires, and used a computer-logging program to continuously rate change in emotional intensity expressed in video clips. Each clip was rated twice to obtain an intra-rater reliability score. The results provide limited support for links between both trait EI and personality variables and how reliably we decode natural expressions of emotion. Limitations and future directions are discussed.

Social Exchange at Work and Emotional Exhaustion: The Role of Personality

Unbalanced social-exchange processes at work have been linked to emotional exhaustion. In addition to organizational factors, individual differences are important determinants of reciprocity perceptions. This study explored whether broad and narrow personality traits were associated with perceived lack of reciprocity (organizational and interpersonal levels), and whether personality moderated the relationship between reciprocity and emotional exhaustion, in a sample of 322 civil servants. Extraversion, agreeableness, emotional stability, internal locus of control, and Type A behavior predicted reciprocity. The relationship between perceived lack of reciprocity with the organization and emotional exhaustion was stronger for individuals reporting lower negative affect or higher extraversion. These findings highlight the importance of personality for understanding perceived reciprocity at work and its impact on emotional exhaustion.

Creating a spontaneous conversational speech corpus

Speech recognition and language analysis of spontaneous speech arising in naturally spoken conversations are becoming the subject of much research. However, there is a shortage of spontaneous speech corpora that are freely available for academics. We therefore undertook the building of a natural conversation speech database, recording over 200 hours of conversations in English by over 600 local university students. With few exceptions, the students used their own cell phones from their own rooms or homes to speak to one another, and they were permitted to speak on any topic they chose. Although they knew that they were being recorded and that they would receive a small payment, their conversations in the corpus are probably very close to being natural and spontaneous. This paper describes a detailed case study of the problems we faced and the methods we used to make the recordings and control the collection of these social science data on a limited budget.

CLOSE—A Data-Driven Approach to Speech Separation

This paper studies single-channel speech separation, assuming unknown, arbitrary temporal dynamics for the speech signals to be separated. A data-driven approach is described, which matches each mixed speech segment against a composite training segment to separate the underlying clean speech segments. To advance the separation accuracy, the new approach seeks and separates the longest mixed speech segments with matching composite training segments. Lengthening the mixed speech segments to match reduces the uncertainty of the constituent training segments, and hence the error of separation. For convenience, we call the new approach Composition of Longest Segments, or CLOSE. The CLOSE method includes a data-driven approach to model long-range temporal dynamics of speech signals, and a statistical approach to identify the longest mixed speech segments with matching composite training segments. Experiments are conducted on the Wall Street Journal database, for separating mixtures of two simultaneous large-vocabulary speech utterances spoken by two different speakers. The results are evaluated using various objective and subjective measures, including the challenge of large-vocabulary continuous speech recognition. It is shown that the new separation approach leads to significant improvement in all these measures.