<p>    </p> <p>Lam, Luchcha. M.S., Purdue University, May 2023. Believe in the Sound You See: The Effects of Body Type and Voice Pitch on the Perceived Audio-Visual Correspondence and Believability of Virtual Characters. Major Professor: Nicoletta Adamo. </p> <p>We examined the effects of body type and voice pitch of virtual characters’ on perceived audio-visual correspondence and believability. For our within-group study, we developed nine experimental conditions using a 3 (body type: ectomorph vs. mesomorph vs. endo- morph body types) × 3 (voice pitch: low vs. medium vs. high fundamental frequency [F0]). We found significant main effects from voice pitch and significant interaction effects between a character’s body type and voice pitch on both the level of perceived audio-visual correspondence and believability of female and male characters. For female characters, we also observed an additional significant main effect from body type and a significant interac- tion effect between the participant’s biological sex and the character’s voice pitch on both perceived audio-visual correspondence and believability. Moreover, the results show that perceived believability is highly correlated to perceived audio-visual correspondence. Our findings have important practical implications in applications where the character is meant to be an emotional or informational guide that requires some level of believability, as the findings suggest that it is possible to enhance the believability of the characters by generating appropriate voices through pitch manipulation of existing voices. </p>

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Dans le cadre de cette thèse, nous proposons une prothèse de mémoire « intelligente », appelée CAPTAIN MEMO, destinée aux malades d’Alzheimer, pour pallier leurs problèmes mnésiques. Cette prothèse est basée sur l’ontologie temporelle, floue et multilingue appelée MemoFuzzyOnto.Cette prothèse offre des interfaces accessibles à cette classe particulière d’utilisateurs. Nous proposons, pour mettre en œuvre ces interfaces, une méthodologie de conception appelée InterfaceToAlz pour concevoir des interfaces accessibles aux malades d’Alzheimer, et qui offre un guide de 146 bonnes pratiques ergonomiques. De plus, nous proposons un outil de visualisation d’ontologies appelé Memo Graph qui génère un graphe dont la visualisation et la manipulation sont accessibles aux malades d’Alzheimer. Cette proposition est motivée par le fait que CAPTAIN MEMO a besoin de générer et d’éditer le graphe de la famille et de l’entourage du patient, à partir de l’ontologie MemoFuzzyOnto qui structure sa base de connaissances. Memo Graph est fondé sur notre guide de bonnes pratiques ergonomiques et notre approche, appelée Incremental Key-Instances Extraction and Visualisation, qui permet une extraction et une visualisation incrémentale du résumé des assertions ABox de l’ontologie. Il supporte également la visualisation des données ouvertes liées (Linked Data) et le passage à l’échelle. Par ailleurs, nous proposons, dans le cadre de cette thèse, une typologie de l’imperfection des données saisies (principalement due à la discordance mnésique provoquée par la maladie), et une méthodologie pour permettre à CAPTAIN MEMO d’être tolérante à la saisie des données fausses. Nous proposons un modèle d’évaluation de la crédibilité et une approche, nommée Data Believability Estimation for Applications to Alzheimer Patients, permettant d’estimer qualitativement et quantitativement la crédibilité de chaque donnée saisie. Enfin, pour que CAPTAIN MEMO soit tolérante à la saisie des intervalles temporels imprécis nous proposons deux approches : l’une basée sur un environnement précis et l’autre basée sur un environnement flou. Dans chacune des deux approches, nous étendons l’approche 4D-fluents pour représenter les intervalles temporels imprécis et les relations temporelles qualitatives, puis nous étendons l’algèbre d’Allen pour prendre en compte les intervalles imprécis dans le cadre de notre ontologie MemoFuzzyOnto. Nos contributions sont implémentées et évaluées. Nous avons évalué l’accessibilité de ses interfaces utilisateurs, le service de CAPTAIN MEMO qui a pour but de stimuler la mémoire du patient, notre approche pour l’estimation quantitative de la crédibilité des données saisies ainsi que la visualisation du graphe générée à l’aide de Memo Graph. Nous avons également évalué la performance de Memo Graph et son utilisabilité par des experts du domaine. / In the context of this thesis, we propose a “smart” memory prosthesis, called CAPTAIN MEMO, to help Alzheimer’s disease patients to palliate mnesic problems. It is based on a temporal, fuzzy and multilingual ontology named MemoFuzzyOnto. It provides accessible user interfaces to this demographic. To design these interfaces, we propose a methodology named InterfaceToAlz which serves as an information base for guiding and evaluating the design of user interfaces for Alzheimer’s disease patients. It identifies 146 design guidelines.Besides, we propose an ontology visualization tool called Memo Graph which offers an accessible and understandable visualization to Alzheimer’s disease patients. In fact, in the context of CAPTAIN MEMO, there is a need to generate the patient entourage/family tree from its personal data structured according to MemoFuzzyOnto. Memo Graph is based on our design guidelines and our approach, named Incremental Key-Instances Extraction and Visualisation, to extract and visualize descriptive instance summarizations from a given ontology and generate “summary instance graphs” from the most important data. It supports Linked Data visualization and scaling.Furthermore, we propose a typology of the imperfection of the data entered (mainly due to the memory discordance caused by this disease), and a methodology to allow false data entry. We propose a believability model and an approach called Data Believability Estimation for Applications to Alzheimer Patients to estimate qualitatively and quantitatively the believability of each data entered. Finally, CAPTAIN MEMO allows imprecise time intervals entry. We propose two approaches: a crisp-based approach and a fuzzy-based approach. The first one uses only crisp standards and tools and is modeled in OWL 2. The second approach is based on fuzzy sets theory and fuzzy tools and is modeled in Fuzzy-OWL 2. For the two approaches, we extend the 4D-fluents model to represent imprecise time intervals and qualitative interval relations. Then, we extend the Allen’s interval algebra to compare imprecise time interval in the context of MemoFuzzyOnto. Our contributions are implemented and evaluated. We evaluated the service of CAPTAIN MEMO which has the aim to stimulate the patient’s memory, the accessibility of its user interfaces, the efficiency of our approach to estimate quantitatively the believability of each data entered and the visualization generated with Memo Graph. We also evaluated Memo Graph with domain expert users.

Based on previous research on spatial attributes in foley and the concept that auditory immersion in first-person perspective computer games is enhanced by believable sound effects, this study explores if there is a connection between stereo foley and the believability of the first-person perspective, and regardless, if there is a preference to either mono or stereo foley. An interactive listening test was created in unreal engine 4, where 20 subjects, all considered gamers, played three levels that differed visually and in auditory content. In these levels, subjects auditioned two versions of avatar-related foley sounds. One version was mono, the other stereo. The test prompted the subjects to complete two tasks for each level, whereupon the foley version changed upon completion of the first task. The subjects then answered questions in between each level, regarding the foley version. They were asked to rate believability and choose a preference, as well as provide motivations for their choices. The quantitative data showed next no evidence that either mono or stereo was generally perceived as more believable or preferred. However, the qualitative data indicates that the majority of players tend to prefer and rate stereo foley as more believable in certain game environments. Furthermore, the data indicates that some subjects prefer a sensory replication of reality in foley. It is also shown that preference for stereo width vary between subjects and therefore argued that there cannot be a perfect standardized setting for stereo foley.

Une part importante de l’activité de communication humaine est dédiée au récit d’événements (fictifs ou non). Ces récits doivent être cohérents et intéressants pour être pertinents. Dans le domaine de la génération automatique de récits, la question de l’intérêt a souvent été négligée, ou traitée via l’utilisation de méthodes ad hoc, au profit de la cohérence des structures narratives produites. Nous proposons d’aborder le processus de création des récits sous l’angle de la modélisation quantitative de critères de pertinence narrative via l’application d’un modèle cognitif de l’intérêt événementiel. Nous montrerons que cet effort de modélisation peut servir de guide pour concevoir un modèle cognitivement plausible de génération de narrations. / Humans devote a considerable amount of time to producing narratives. Whatever a story is used for (whether to entertain or to teach), it must be relevant. Relevant stories must be believable and interesting. The field of computational generation of narratives has explored many ways of generating narratives, especially well-formed and understandable ones. The question of what makes a story interesting has however been largely ignored or barely addressed. Only some specific aspects of narrative interest have been considered. No general theoretical framework that would serve as guidance for the generation of interesting and believable narratives has been provided. The aim of this thesis is to introduce a cognitive model of situational interest and use it to offer formal criteria to decide to what extent a story is relevant. Such criteria could guide the development of a cognitively plausible model of story generation.