Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition

We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators also contain emotional implication but were regarded as neutral expressions by the previous interpretation. In this paper, we employ latent semantic analysis to perform topic theme detection and identify target audiences for such inputs. We also discuss how such semantic interpretation of the dialog contexts is used to interpret affect more appropriately during virtual improvisation. Also, in order to build a reliable affect analyser, it is important to detect and combine weak affect indicators from other channels such as body language. Such emotional body language detection also provides a nonintrusive channel to detect users’ experience without interfering with the primary task. Thus, we also make initial exploration on affect detection from several universally accepted emotional gestures

Epenthesis: The Movement of the Urdu Alveolar-Fricative Sound into the Punjabi Palatal-Affricate Sound

Pakistan is a multilingual country where the Urdu language serves as lingua franca. Although Urdu is the national and official language of Pakistan, it bears the status of the second language (L2) in most of the regions due to the dominance of regional languages. The Punjabi language is the first language (L1) of the people of Punjab. This study intends to investigate the interlanguage influence and extralinguistic factors of phonological variants produced in the process of epenthesis of Punjabi palatal-affricate (/dʒ/) with the deletion of Urdu alveolar-fricative (/z/). The analysis of this study has been conducted using PRAAT software which proved that the native Punjabi speakers replace the /z/ sound with the /dʒ/ sound no matter if it occurs at the start, middle, or the end of a word. Moreover, this process of epenthesis is the result of the influence of the native language, i.e. Punjabi. The outcome of the analysis indicates that the gender and dwelling (urban or rural) of the participants have nothing to do with epenthesis. However, the education of the participants is the main reason for epenthesis

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

FINE-GRAINED EMOTION DETECTION IN MICROBLOG TEXT

Automatic emotion detection in text is concerned with using natural language processing techniques to recognize emotions expressed in written discourse. Endowing computers with the ability to recognize emotions in a particular kind of text, microblogs, has important applications in sentiment analysis and affective computing. In order to build computational models that can recognize the emotions represented in tweets we need to identify a set of suitable emotion categories. Prior work has mainly focused on building computational models for only a small set of six basic emotions (happiness, sadness, fear, anger, disgust, and surprise). This thesis describes a taxonomy of 28 emotion categories, an expansion of these six basic emotions, developed inductively from data. This set of 28 emotion categories represents a set of fine-grained emotion categories that are representative of the range of emotions expressed in tweets, microblog posts on Twitter. The ability of humans to recognize these fine-grained emotion categories is characterized using inter-annotator reliability measures based on annotations provided by expert and novice annotators. A set of 15,553 human-annotated tweets form a gold standard corpus, EmoTweet-28. For each emotion category, we have extracted a set of linguistic cues (i.e., punctuation marks, emoticons, emojis, abbreviated forms, interjections, lemmas, hashtags and collocations) that can serve as salient indicators for that emotion category. We evaluated the performance of automatic classification techniques on the set of 28 emotion categories through a series of experiments using several classifier and feature combinations. Our results shows that it is feasible to extend machine learning classification to fine-grained emotion detection in tweets (i.e., as many as 28 emotion categories) with results that are comparable to state-of-the-art classifiers that detect six to eight basic emotions in text. Classifiers using features extracted from the linguistic cues associated with each category equal or better the performance of conventional corpus-based and lexicon-based features for fine-grained emotion classification. This thesis makes an important theoretical contribution in the development of a taxonomy of emotion in text. In addition, this research also makes several practical contributions, particularly in the creation of language resources (i.e., corpus and lexicon) and machine learning models for fine-grained emotion detection in text

‘Setting the Scene’:A More-Than-Representational, Participatory Action Study Exploring the Wellbeing Benefits of Participatory Arts for People Living with Dementia and their Carers

Community-based participatory arts are being increasingly promoted for the wellbeing of people living with dementia and their carers. Yet, there remains variability in the arts-based programmes available, inconsistencies in how they are evaluated, and ambiguity around wellbeing definitions. Moreover, the voices of people with dementia are lacking in the research process. This ESRC-funded CASE project collaborated with Theatre by the Lake, Cumbria, to examine the effectiveness of their ‘Setting the Scene’ participatory multi-arts programme. The project involved a participatory action research (PAR) and sensory ethnography design, with qualitative and visual multi-methods. An ‘in the moment’ theoretical lens was developed by integrating more-than-representational theory, therapeutic landscapes and relational wellbeing concepts. Four resulting empirical chapters illustrate how people with dementia and carers contributed to, and were benefited by, Setting the Scene’s arts, objects, people and landscapes. The first chapter explores person-centred, ‘in the moment’ and strength-based engagements, elicited by the programme’s multi-arts, multi-modal, and thematic design. The following chapter examines the plurality of communication and participation in art-making through more-than-verbal, more-than-human tenets. The final two chapters examine the nuances of therapeutic landscapes and acts of caring within the programme, respectively. Overall, this thesis considers participatory multi-arts for enabling socio-spatial-material therapeutic encounters through emergent, non-judgemental, creative landscapes. Setting the Scene is understood as producing important ‘in the moment’ relational wellbeing benefits for people impacted by dementia, alongside the joint respite potential for carers. New contributions are made to a more-than-verbal reconceptualization of ‘voice’ to support the inclusivity of people with dementia in research and practice. Through novel integration of ‘more-than’ theories and methods so far lacking in dementia research, this thesis demonstrates how people with dementia can be acknowledged as ‘more than’ their symptoms through the arts; being recognised for enduring skills, narratives and authenticities that contribute to ‘being’ and ‘doing’ well

The Relationship Between Teacher Efficacy and Multiple Learning Competencies with Arts and Non-Arts Educators

The National Commission on Excellence in Education (1983) published A Nation at Risk to relay the academic performance level of American students. The results revealed that Americans students were performing considerably below other countries. Consequently, accountability through testing became the focus for policy makers to promote educational reform and educational equality (Linn, 2000). The focus on testing, however, has hindered student achievement and led to more (a) social promotion; (b) remedial courses; (c) retention rates; (d) teachers leaving the field; (e) dropout rates; and (f) invalid achievement results (Hoffinan, 2001). As more schools have reassigned staff members to meet the demands of testing and have altered the school curriculum to cover the academic standards being tested, art programs and teachers have been removed from schools across the nation. The elimination of the arts in the curriculum, nevertheless, has not proven to be a remedy for improving student achievement. The average reading score for fourth and eighth graders has only increased by two points, since 2005 and four points compared to the first assessment 15 years ago (National Assessment of Educational Progress, 2007). The literature review on the impact of the arts on learning clearly supports the implementation of the arts to improve student achievement and the overall quality of education. The results of one particular research study at UCLA revealed that students involved in the arts were more successful in school than those who were not involved (Caterall et al., 1999). The theory of multiple intelligences (Gardner, 1999) encompassed the essence of the creative genius of artists. People were more inclined to learn when involved in an activity for which they have talent due to the arts: (a) providing powerful points of entry; (b) offering models; and (c) providing multiple representations of the central idea (Gardner, 1999). The gap in the literature suggested that researchers had not explored the impact that the multiple intelligences of teachers had on the effectiveness of learning, which in turn, could raise student achievement. The purpose, therefore, of this non-experimental study was to examine whether the multiple intelligences of art and non-arts teachers, measured by the Multiple Intelligences Test (Chislet & Chapman, 2005), impacted teachers\u27 perceptions of teacher efficacy, measured by the Teachers\u27 Sense of Efficacy Scale Test (Tschannen-Moran & Hoy, 2001). The accessible population was Palm Beach County K-12 teachers who responded to the surveys online. The researcher ran the following statistical tests into the Statistical Package for the Social Sciences (SPSS) Version 14.0: (a) Cronbach\u27s Alpha to determine the reliability estimates; (b) Pearson\u27s Chi-Square Test to observe frequency distributions; (c) Correlation Matrix to determine the degree of the relationship between groups; (d) Multiple Regressions to ascertain the criterion-related validity; (e) ANOVAS to establish the means of each group; and (f) t tests to establish whether the difference of the means were statistically significant. The outcomes of the study will provide additional information for the body of research that supports the inclusion of the arts as an indispensable element of the school\u27s curriculum for (a) raising the quality of instruction and (b) providing a more equitable education for American students