Semi-Automated & Collaborative Online Training Module For Improving Communication Skills

This paper presents a description and evaluation of the ROC Speak system, a platform that allows ubiquitous access to communication skills training. ROC Speak (available at rocspeak.com) enables anyone to go to a website, record a video, and receive feedback on smile intensity, body movement, volume modulation, filler word usage, unique word usage, word cloud of the spoken words, in addition to overall assessment and subjective comments by peers. Peer comments are automatically ranked and sorted for usefulness and sentiment (i.e., positive vs. negative). We evaluated the system with a diverse group of 56 online participants for a 10-day period. Participants submitted responses to career oriented prompts every other day. The participants were randomly split into two groups: 1) treatment - full feedback from the ROC Speak system; 2) control - written feedback from online peers. When judged by peers (p<.001) and independent raters (p<.05), participants from the treatment group demonstrated statistically significant improvement in overall speaking skills rating while the control group did not. Furthermore, in terms of speaking attributes, treatment group showed an improvement in friendliness (p<.001), vocal variety (p<.05) and articulation (p<.01)

Semi-Automated & Collaborative Online Training Module For Improving Communication Skills

This is the author accepted manuscript. The final version is available from ACM via the DOI in this recordThis paper presents a description and evaluation of the ROC Speak system, a platform that allows ubiquitous access to communication skills training. ROC Speak (available at rocspeak.com) enables anyone to go to a website, record a video, and receive feedback on smile intensity, body movement, volume modulation, filler word usage, unique word usage, word cloud of the spoken words, in addition to overall assessment and subjective comments by peers. Peer comments are automatically ranked and sorted for usefulness and sentiment (i.e., positive vs. negative). We evaluated the system with a diverse group of 56 online participants for a 10-day period. Participants submitted responses to career oriented prompts every other day. The participants were randomly split into two groups: 1) treatment - full feedback from the ROC Speak system; 2) control - written feedback from online peers. When judged by peers (p<.001) and independent raters (p<.05), participants from the treatment group demonstrated statistically significant improvement in overall speaking skills rating while the control group did not. Furthermore, in terms of speaking attributes, treatment group showed an improvement in friendliness (p<.001), vocal variety (p<.05) and articulation (p<.01)

Multi-modal post-editing of machine translation

As MT quality continues to improve, more and more translators switch from traditional translation from scratch to PE of MT output, which has been shown to save time and reduce errors. Instead of mainly generating text, translators are now asked to correct errors within otherwise helpful translation proposals, where repetitive MT errors make the process tiresome, while hard-to-spot errors make PE a cognitively demanding activity. Our contribution is three-fold: first, we explore whether interaction modalities other than mouse and keyboard could well support PE by creating and testing the MMPE translation environment. MMPE allows translators to cross out or hand-write text, drag and drop words for reordering, use spoken commands or hand gestures to manipulate text, or to combine any of these input modalities. Second, our interviews revealed that translators see value in automatically receiving additional translation support when a high CL is detected during PE. We therefore developed a sensor framework using a wide range of physiological and behavioral data to estimate perceived CL and tested it in three studies, showing that multi-modal, eye, heart, and skin measures can be used to make translation environments cognition-aware. Third, we present two multi-encoder Transformer architectures for APE and discuss how these can adapt MT output to a domain and thereby avoid correcting repetitive MT errors.Angesichts der stetig steigenden Qualität maschineller Übersetzungssysteme (MÜ) post-editieren (PE) immer mehr Übersetzer die MÜ-Ausgabe, was im Vergleich zur herkömmlichen Übersetzung Zeit spart und Fehler reduziert. Anstatt primär Text zu generieren, müssen Übersetzer nun Fehler in ansonsten hilfreichen Übersetzungsvorschlägen korrigieren. Dennoch bleibt die Arbeit durch wiederkehrende MÜ-Fehler mühsam und schwer zu erkennende Fehler fordern die Übersetzer kognitiv. Wir tragen auf drei Ebenen zur Verbesserung des PE bei: Erstens untersuchen wir, ob andere Interaktionsmodalitäten als Maus und Tastatur das PE unterstützen können, indem wir die Übersetzungsumgebung MMPE entwickeln und testen. MMPE ermöglicht es, Text handschriftlich, per Sprache oder über Handgesten zu verändern, Wörter per Drag & Drop neu anzuordnen oder all diese Eingabemodalitäten zu kombinieren. Zweitens stellen wir ein Sensor-Framework vor, das eine Vielzahl physiologischer und verhaltensbezogener Messwerte verwendet, um die kognitive Last (KL) abzuschätzen. In drei Studien konnten wir zeigen, dass multimodale Messung von Augen-, Herz- und Hautmerkmalen verwendet werden kann, um Übersetzungsumgebungen an die KL der Übersetzer anzupassen. Drittens stellen wir zwei Multi-Encoder-Transformer-Architekturen für das automatische Post-Editieren (APE) vor und erörtern, wie diese die MÜ-Ausgabe an eine Domäne anpassen und dadurch die Korrektur von sich wiederholenden MÜ-Fehlern vermeiden können.Deutsche Forschungsgemeinschaft (DFG), Projekt MMP

Factors in the identification and treatment of stuttering.

A large number of children with a diagnosis of stuttering will recover, often without formal treatment. This recovery pattern highlights the importance of a clear, early diagnosis and has implications for therapeutic practice. This thesis investigated three factors that could assist speech and language therapists in their diagnosis and treatment of children who stutter (CWS). Those factors were social, motor and speech skills. A pilot study investigating a fourth factor, communication attitude, is reported as an appendix. All factors were investigated from the perspective of the EXPLAN model of fluency failure. EXPLAN suggests that a combination of speech timing and phonological difficulty is an important source of fluency failures. The investigation into the social skills of CWS indicated that there is a trend for CWS to hold a lower social position to that of age matched controls. CWS were more likely to be bullied at school than their peers. The relationship between stuttering severity and social status was not significant. The motor skills study, using a battery of tests of cerebellar function (Dow & Moruzzi, 1958), indicated that CWS showed a deficit in performance on balance/posture tests at a young age and on complex movement tasks at teenage when compared to age matched controls. These differences are discussed with relation to auditory and cerebellar function. The fluency of a group of CWS was examined using phonological word analysis (Au-Yeung & Howell, 1998). Five children were producing predominantly part- word repetitions at initial assessment. Four of these children had persisted in their stutter when followed up three years later. Results suggest that information regarding motor skills and linguistic analysis of speech may be useful in the diagnosis and treatment of CWS. The results of the experimental work are discussed with relation to their theoretical and clinical significance

Improving classification of posture based attributed attention assessed by ranked crowd-raters

Attribution of attention from observable body posture is plausible, providing additional information for affective computing applications. We previously reported a promissory 69. 72 ± 10. 50 (μ ± σ) of F-measure to use posture as a proxy for attributed attentional state with implications for affective computing applications. Here, we aim at improving that classification rate by reweighting votes of raters giving higher confidence to those raters that are representative of the raters population. An increase to 75. 35 ± 11. 66 in F-measure was achieved. The improvement in predictive power by the classifier is welcomed and its impact is still being assessed

Deep into that darkness, peering: A series of studies on the Dark Triad of personality

This submission spans my work undertaken over the course of recent years on sub-clinical narcissism, Machiavellianism, and sub-clinical psychopathy: The Dark Triad of personality. Across this thesis, I present a series of published and unpublished materials that cover these overlapping yet distinct personality traits in relation to their attractiveness to women, short- and long-term mating preferences, broader personality and lifestyle correlates, general and sexual competitiveness (in women), verbal and non-verbal behavioural outcomes in a mate-attraction scenario, and health-related behaviours and longevity. I also apply a form of scale analysis to establish how well these traits are measured across sex and age groups by a short inventory that has seen widespread use in the field. Broadly, I consider these issues against a backdrop of evolutionary psychology, individual differences in personality, sex- and age-related differences, and the perception and measurement of personality traits. Specifically, I consider the need to look beyond self-reports, especially when over-claiming is a serious risk, to simultaneously evaluate sex similarities, as well as sex differences, to develop an understanding of the particular behaviours that are demonstrated by individuals with personalities associated with higher levels of mating success, and the need to subject inventories to rigorous scrutiny, across both classical, and item response testing. In each chapter, I have sought to contribute to the on-going discussions that researchers active in this field are engaged with regarding the future of this rapidly-advancing area of study. Interest in this personality constellation shows no sign of abating – its rise to prominence within evolutionary and personality psychology to date has been swift – and I conclude with thoughts and suggestions as to which areas future research could explore in order to further our understanding of the Dark Triad

Mobility classification of cattle with micro-Doppler radar

Lameness in dairy cattle is a welfare concern that negatively impacts animal productivity and farmer profitability. Micro-Doppler radar sensing has been previously suggested as a potential system for automating lameness detection in ruminants. This thesis investigates the refinement of the proposed automated system by analysing and enhancing the repeatability and accuracy of the existing scoring method in cattle mobility scoring, used to provide labels in machine learning. The main aims of the thesis were (1) to quantify the performance of the micro-Doppler radar sensing method for the assessment of mobility, (2) to characterise and validate micro-Doppler radar signatures of dairy cattle with varying degrees of gait impairment, and (3) to develop machine learning algorithms that can infer the mobility status of the animals under test from their radar signatures and support automatic contactless classification. The first study investigated inter-assessor agreement using a 4-level system and modifications to it, as well as the impact of factors such as mobility scoring experience, confidence in scoring decisions, and video characteristics. The results revealed low levels of agreement between assessors' scores, with kappa values ranging from 0.16 to 0.53. However, after transforming and reducing the mobility scoring system levels, an improvement was observed, with kappa values ranging from 0.2 to 0.67. Subsequently, a longitudinal study was conducted using good-agreement scores as ground truth labels in supervised machine-learning models. However, the accuracy of the algorithmic models was found to be insufficient, ranging from 0.57 to 0.63. To address this issue, different labelling systems and data pre-processing techniques were explored in a cross-sectional study. Nonetheless, the inter-assessor agreement remained challenging, with an average kappa value of 0.37 (SD = 0.16), and high-accuracy algorithmic predictions remained elusive, with an average accuracy of 56.1 (SD =16.58). Finally, the algorithms' performance was tested with high-confidence labels, which consisted of only scores 0 and 3 of the AHDB system. This testing resulted in good classification accuracy (0.82), specificity (0.79), and sensitivity (0.85). This led to the proposal of a new approach to producing labels, testing vantage point changes, and improving the performance of machine learning models (average accuracy = 0.7 & SD = 0.17, average sensitivity = 0.68 & SD = 0.27, average specificity = 0.75 & SD = 0.17). The research identified a challenge in creating high-confidence diagnostic labels for supervised machine learning-based algorithms to automate the detection and classification of lameness in dairy cows. As a result, the original goals were partially overridden, with the focus shifted to creating reliable labels that would perform well with radar data and machine learning. This point was considered necessary for smooth system development and process automation. Nevertheless, we managed to quantify the performance of the micro-Doppler radar system, partially develop the supervised machine learning algorithms, compare levels of agreement among multiple assessors, evaluate the assessment tools, assess the mobility evaluation process and gather a valuable data set which can be used as a foundation for subsequent studies. Finally, the thesis suggests changes in the assessment process to improve the prediction accuracy of algorithms based on supervised machine learning with radar data

Analyse et synthèse de mouvements théâtraux expressifs

This thesis addresses the analysis and generation of expressive movements for virtual human character. Based on previous results from three different research areas (perception of emotions and biological motion, automatic recognition of affect and computer character animation), a low-dimensional motion representation is proposed. This representation consists of the spatio-temporal trajectories of end-effectors (i.e., head, hands and feet), and pelvis. We have argued that this representation is both suitable and sufficient for characterizing the underlying expressive content in human motion, and for controlling the generation of expressive whole-body movements. In order to prove these claims, this thesis proposes: (i) A new motion capture database inspired by physical theory, which contains three categories of motion (locomotion, theatrical and improvised movements), has been built for several actors; (ii) An automatic classification framework has been designed to qualitatively and quantitatively assess the amount of emotion contained in the data. It has been shown that the proposed low-dimensional representation preserves most of the motion cues salient to the expression of affect and emotions; (iii) A motion generation system has been implemented, both for reconstructing whole-body movements from the low-dimensional representation, and for producing novel end-effector expressive trajectories. A quantitative and qualitative evaluation of the generated whole body motions shows that these motions are as expressive as the movements recorded from human actors.Cette thèse porte sur l'analyse et la génération de mouvements expressifs pour des personnages humains virtuels. Sur la base de résultats de l’état de l’art issus de trois domaines de recherche différents - la perception des émotions et du mouvement biologique, la reconnaissance automatique des émotions et l'animation de personnages virtuels - une représentation en faible dimension des mouvements constituée des trajectoires spatio-temporelles des extrémités des chaînes articulées (tête, mains et pieds) et du pelvis a été proposée. Nous avons soutenu que cette représentation est à la fois appropriée et suffisante pour caractériser le contenu expressif du mouvement humain et pour contrôler la génération de mouvements corporels expressifs. Pour étayer cette affirmation, cette thèse propose:i) une nouvelle base de données de capture de mouvements inspirée par la théorie du théâtre physique. Cette base de données contient des exemples de différentes catégories de mouvements (c'est-à-dire des mouvements périodiques, des mouvements fonctionnels, des mouvements spontanés et des séquences de mouvements théâtraux), produits avec des états émotionnels distincts (joie, tristesse, détente, stress et neutre) et interprétés par plusieurs acteurs.ii) Une étude perceptuelle et une approche basée classification automatique conçus pour évaluer qualitativement et quantitativement l'information liée aux émotions véhiculées et encodées dans la représentation proposée. Nous avons observé que, bien que de légères différences dans la performance aient été trouvées par rapport à la situation où le corps entier a été utilisé, notre représentation conserve la plupart des marqueurs de mouvement liés à l'expression de laffect et des émotions.iii) Un système de synthèse de mouvement capable : a) de reconstruire des mouvements du corps entier à partir de la représentation à faible dimension proposée et b) de produire de nouvelles trajectoires extrémités expressives (incluant la trajectoire du bassin). Une évaluation quantitative et qualitative des mouvements du corps entier générés montre que ces mouvements sont aussi expressifs que les mouvements enregistrés à partir d'acteurs humains

The frequency of falls in children judo training

Purpose: Falling techniques are inseparable part of youth judo training. Falling techniques are related to avoiding injuries exercises (Nauta et al., 2013). There is not good evidence about the ratio of falling during the training in children. Methods: 26 children (age 8.88±1.88) were video recorded on ten training sessions for further indirect observation and performance analysis. Results: Research protocol consisted from recording falls and falling techniques (Reguli et al., 2015) in warming up, combat games, falling techniques, throwing techniques and free fighting (randori) part of the training session. While children were taught almost exclusively forward slapping roll, backward slapping roll and sideward direct slapping fall, in other parts of training also other types of falling, as forward fall on knees, naturally occurred. Conclusions: Judo coaches should stress also on teaching unorthodox falls adding to standard judo curriculum (Koshida et al., 2014). Various falling games to teach children safe falling in different conditions should be incorporated into judo training. Further research to gain more data from groups of different age in various combat and non-combat sports is needed

Fear of crime and victimization among the elderly participating in the self-defence course

Purpose. Self-defence training could enhance seniors´ defensive skills and fitness. There is lack of evidence about fear and concerns of seniors participating in the self-defence course. Methods. 18 elderly persons (16 female, 1 male; age 66.2, SD=5.86) participated in the self-defence course lasting 8 training units (each unit 60 minutes). Standardized tool for fear of crime and victimization analysis previously used in Euro-Justis project in the Czech Republic (2011) was used in pretest and posttest. Results. We explored the highest fear of crime by participants in their residence area after dark (mean=2,77; median=3; SD=0,80), lower fear at the night in their homes (mean=2,29; median=2; SD=0,75) and in their residence area at the daytime (mean=2,00; median=2; SD=0,77) at the beginning of the course. We noticed certain decrease of fear of crime after the intervention. Participant were less afraid of crime in their residence area after dark (mean=2,38; median=2; SD=0,77), they felt lower fear of crime at the night in their homes (mean=2,00; median=2; SD=0,48) and in their residence area at the daytime (mean=1,82; median=2; SD=0,63). Conclusions. The approach to self-defence teaching for elderly should be focused not just on the motor development, but also on their emotional state, fear of crime, perception of dangerousness of diverse situations and total wellbeing. Fear of crime analysis can contribute to create tailor made structure of the self-defence course for specific groups of citizens