Designing Embodied Interactive Software Agents for E-Learning: Principles, Components, and Roles

Embodied interactive software agents are complex autonomous, adaptive, and social software systems with a digital embodiment that enables them to act on and react to other entities (users, objects, and other agents) in their environment through bodily actions, which include the use of verbal and non-verbal communicative behaviors in face-to-face interactions with the user. These agents have been developed for various roles in different application domains, in which they perform tasks that have been assigned to them by their developers or delegated to them by their users or by other agents. In computer-assisted learning, embodied interactive pedagogical software agents have the general task to promote human learning by working with students (and other agents) in computer-based learning environments, among them e-learning platforms based on Internet technologies, such as the Virtual Linguistics Campus (www.linguistics-online.com). In these environments, pedagogical agents provide contextualized, qualified, personalized, and timely assistance, cooperation, instruction, motivation, and services for both individual learners and groups of learners. This thesis develops a comprehensive, multidisciplinary, and user-oriented view of the design of embodied interactive pedagogical software agents, which integrates theoretical and practical insights from various academic and other fields. The research intends to contribute to the scientific understanding of issues, methods, theories, and technologies that are involved in the design, implementation, and evaluation of embodied interactive software agents for different roles in e-learning and other areas. For developers, the thesis provides sixteen basic principles (Added Value, Perceptible Qualities, Balanced Design, Coherence, Consistency, Completeness, Comprehensibility, Individuality, Variability, Communicative Ability, Modularity, Teamwork, Participatory Design, Role Awareness, Cultural Awareness, and Relationship Building) plus a large number of specific guidelines for the design of embodied interactive software agents and their components. Furthermore, it offers critical reviews of theories, concepts, approaches, and technologies from different areas and disciplines that are relevant to agent design. Finally, it discusses three pedagogical agent roles (virtual native speaker, coach, and peer) in the scenario of the linguistic fieldwork classes on the Virtual Linguistics Campus and presents detailed considerations for the design of an agent for one of these roles (the virtual native speaker)

A dynamic multi-application dialog engine for task-oriented voice user interfaces

This thesis introduces the Dymalog framework for spoken language dialog systems, which separates the applications from the actual dialog system. It facilitates the control of a plurality of applications through a single dialog system, changeable during run time. This is achieved by application-independent knowledge processing inside the dialog system, based on a hierarchical representation of obtained information (o²I -Trees). The approach enables the realization of generic dialog functionalities. Dymalog is composed of a collection of components; each serves mainly a single purpose. It fosters the generation of competing hypotheses during the processing of the user input in order to derive an optimal interpretation at a certain stage in the processing. The Marvin dialog system puts Dymalog into practice. We discuss selected interactions with various applications enabled for the operation through the system. The parameterized hypothesis selection process is considered in detail, especially the parameter estimation algorithm Grail, and the same holds for the development process in the generation of competing hypotheses for the user input.Die Arbeit stellt die Grundlagen zur Realisierung des sprachbasierten Dialogsystems Marvin für die Interaktion eines Benutzers mit verschiedenen Applikationen vor: Dymalog. Es erlaubt die Kontrolle unterschiedlicher Applikationen durch ein einziges System und ermöglicht u.a. dynamische Änderungen der verfügbaren Applikationen zur Laufzeit. Dies wird durch applikationsunabhängige Wissensverarbeitung erreicht, basierend auf modularen ontologischen Beschreibungen der Anwendungsfreiheitsgrade (o²I -Trees). Die Trennung von Dialogsystem und Applikationen ermöglicht die Realisierung generischer Dialogfunktionalitäten. Dymalog besteht aus einer Reihe von separaten Einheiten, jede beinhaltet im Wesentlichen ein Modell zur Verarbeitung der Benutzereingabe. Um die optimale Interpretation der Benutzereingabe zu erlangen wird die Generation alternativer Interpretationen gefördert. Das Marvin Dialogsystem realisiert die Konzepte aus Dymalog. Ausgewählte Interaktionen mit verschiedenen Applikationen werden diskutiert. Ferner wird der parameterisierte Auswahlprozeß der \u27besten\u27; Interpretation beleuchtet, insbesondere der Parameter-Schätzalgorithmus Grail, und die Erzeugung alternativer Hypothesen durch ausgewählte Einheiten diskutiert

Real-time generation and adaptation of social companion robot behaviors

Social robots will be part of our future homes. They will assist us in everyday tasks, entertain us, and provide helpful advice. However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate. An essential skill of every social robot is verbal and non-verbal communication. In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine. Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors. In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot. However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems. This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences. Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence. The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning. Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning. It provides a higher-level view from the system designer's perspective and guidance from the start to the end. It illustrates the process of modeling, simulating, and evaluating such adaptation processes. Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness. The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes. They are evaluated in the lab and in in-situ studies. These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor. Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukünftigen Zuhauses sein. Sie werden uns bei alltäglichen Aufgaben unterstützen, uns unterhalten und uns mit hilfreichen Ratschlägen versorgen. Noch gibt es allerdings technische Herausforderungen, die zunächst überwunden werden müssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen. Eine wesentliche Fähigkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation. Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine Verkörperung, die Erwartungen an die Maschine weckt. Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natürliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen. Darüber hinaus müssen Roboter auch die individuellen Vorlieben der Benutzer berücksichtigen. So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprägt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter führt. Roboter haben jedoch keine menschliche Intuition - sie müssen mit entsprechenden Algorithmen für diese Probleme ausgestattet werden. In dieser Arbeit wird der Einsatz von bestärkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die Bedürfnisse und Vorlieben des Benutzers anzupassen. Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern. Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle über die multimodale Verhaltenserzeugung des Roboters, ein Verständnis des menschlichen Feedbacks und eine algorithmische Basis für maschinelles Lernen. Daher wird in dieser Arbeit ein konzeptioneller Rahmen für die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestärkendem Lernen entwickelt. Er bietet eine übergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende. Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse. Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten. Der konzeptionelle Rahmen wird für mehrere Anwendungsfälle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen führt, die in Labor- und In-situ-Studien evaluiert werden. Diese Ansätze befassen sich mit typischen Aktivitäten in häuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der Persönlichkeit, dem Persona, der Höflichkeit und dem Humor des Roboters liegt. In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an

Evaluating humanoid embodied conversational agents in mobile guide applications

Evolution in the area of mobile computing has been phenomenal in the last few years. The exploding increase in hardware power has enabled multimodal mobile interfaces to be developed. These interfaces differ from the traditional graphical user interface (GUI), in that they enable a more “natural” communication with mobile devices, through the use of multiple communication channels (e.g., multi-touch, speech recognition, etc.). As a result, a new generation of applications has emerged that provide human-like assistance in the user interface (e.g., the Siri conversational assistant (Siri Inc., visited 2010)). These conversational agents are currently designed to automate a number of tedious mobile tasks (e.g., to call a taxi), but the possible applications are endless. A domain of particular interest is that of Cultural Heritage, where conversational agents can act as personalized tour guides in, for example, archaeological attractions. The visitors to historical places have a diverse range of information needs. For example, casual visitors have different information needs from those with a deeper interest in an attraction (e.g., - holiday learners versus students). A personalized conversational agent can access a cultural heritage database, and effectively translate data into a natural language form that is adapted to the visitor’s personal needs and interests. The present research aims to investigate the information needs of a specific type of visitors, those for whom retention of cultural content is important (e.g., students of history, cultural experts, history hobbyists, educators, etc.). Embodying a conversational agent enables the agent to use additional modalities to communicate this content (e.g., through facial expressions, deictic gestures, etc.) to the user. Simulating the social norms that guide the real-world human-to-human interaction (e.g., adapting the story based on the reactions of the users), should at least theoretically optimize the cognitive accessibility of the content. Although a number of projects have attempted to build embodied conversational agents (ECAs) for cultural heritage, little is known about their impact on the users’ perceived cognitive accessibility of the cultural heritage content, and the usability of the interfaces they support. In particular, there is a general disagreement on the advantages of multimodal ECAs in terms of users’ task performance and satisfaction over nonanthropomorphised interfaces. Further, little is known about what features influence what aspects of the cognitive accessibility of the content and/or usability of the interface. To address these questions I studied the user experiences with ECA interfaces in six user studies across three countries (Greece, UK and USA). To support these studies, I introduced: a) a conceptual framework based on well-established theoretical models of human cognition, and previous frameworks from the literature. The framework offers a holistic view of the design space of ECA systems b) a research technique for evaluating the cognitive accessibility of ECA-based information presentation systems that combine data from eye tracking and facial expression recognition. In addition, I designed a toolkit, from which I partially developed its natural language processing component, to facilitate rapid development of mobile guide applications using ECAs. Results from these studies provide evidence that an ECA, capable of displaying some of the communication strategies (e.g., non-verbal behaviours to accompany linguistic information etc.) found in the real-world human guidance scenario, is not affecting and effective in enhancing the user’s ability to retain cultural content. The findings from the first two studies, suggest than an ECA has no negative/positive impact on users experiencing content that is similar (but not the same) across different locations (see experiment one, in Chapter 7), and content of variable difficulty (see experiment two, in Chapter 7). However, my results also suggest that improving the degree of content personalization and the quality of the modalities used by the ECA can result in both effective and affecting human-ECA interactions. Effectiveness is the degree to which an ECA facilitates a user in accomplishing the navigation and information tasks. Similarly, affecting is the degree to which the ECA changes the quality of the user’s experience while accomplishing the navigation and information tasks. By adhering to the above rules, I gradually improved my designs and built ECAs that are affecting. In particular, I found that an ECA can affect the quality of the user’s navigation experience (see experiment three in Chapter 7), as well as how a user experiences narrations of cultural value (see experiment five, in Chapter 8). In terms of navigation, I found sound evidence that the strongest impact of the ECAs nonverbal behaviours is on the ability of users to correctly disambiguate the navigation of an ECA instructions provided by a tour guide system. However, my ECAs failed to become effective, and to elicit enhanced navigation or retention performances. Given the positive impact of ECAs on the disambiguation of navigation instructions, the lack of ECA-effectiveness in navigation could be attributed to the simulated mobile conditions. In a real outdoor environment, where users would have to actually walk around the castle, an ECA could have elicited better navigation performance, than a system without it. With regards to retention performance, my results suggest that a designer should not solely consider the impact of an ECA, but also the style and effectiveness of the question-answering (Q&A) with the ECA, and the type of user interacting with the ECA (see experiments four and six, in Chapter 8). I found that that there is a correlation between how many questions participants asked per location for a tour, and the information they retained after the completion of the tour. When participants were requested to ask the systems a specific number of questions per location, they could retain more information than when they were allowed to freely ask questions. However, the constrained style of interaction decreased their overall satisfaction with the systems. Therefore, when enhanced retention performance is needed, a designer should consider strategies that should direct users to ask a specific number of questions per location for a tour. On the other hand, when maintaining the positive levels of user experiences is the desired outcome of an interaction, users should be allowed to freely ask questions. Then, the effectiveness of the Q&A session is of importance to the success/failure of the user’s interaction with the ECA. In a natural-language question-answering system, the system often fails to understand the user’s question and, by default, it asks the user to rephrase again. A problem arises when the system fails to understand a question repeatedly. I found that a repetitive request to rephrase the same question annoys participants and affects their retention performance. Therefore, in order to ensure effective human-ECA Q&A, the repeat messages should be built in a way to allow users to figure out how to ask the system questions to avoid improper responses. Then, I found strong evidence that an ECA may be effective for some type of users, while for some others it may be not. I found that an ECA with an attention-grabbing mechanism (see experiment six, in Chapter 8), had an inverse effect on the retention performance of participants with different gender. In particular, it enhanced the retention performance of the male participants, while it degraded the retention performance of the female participants. Finally, a series of tentative design recommendations for the design of both affecting and effective ECAs in mobile guide applications in derived from the work undertaken. These are aimed at ECA researchers and mobile guide designers

SiAM-dp : an open development platform for massively multimodal dialogue systems in cyber-physical environments

Cyber-physical environments enhance natural environments of daily life such as homes, factories, offices, and cars by connecting the cybernetic world of computers and communication with the real physical world. While under the keyword of Industrie 4.0, cyber-physical environments will take a relevant role in the next industrial revolution, and they will also appear in homes, offices, workshops, and numerous other areas. In this new world, classical interaction concepts where users exclusively interact with a single stationary device, PC or smartphone become less dominant and make room for new occurrences of interaction between humans and the environment itself. Furthermore, new technologies and a rising spectrum of applicable modalities broaden the possibilities for interaction designers to include more natural and intuitive non-verbal and verbal communication. The dynamic characteristic of a cyber-physical environment and the mobility of users confronts developers with the challenge of developing systems that are flexible concerning the connected and used devices and modalities. This implies new opportunities for cross-modal interaction that go beyond dual modalities interaction as is well known nowadays. This thesis addresses the support of application developers with a platform for the declarative and model based development of multimodal dialogue applications, with a focus on distributed input and output devices in cyber-physical environments. The main contributions can be divided into three parts: - Design of models and strategies for the specification of dialogue applications in a declarative development approach. This includes models for the definition of project resources, dialogue behaviour, speech recognition grammars, and graphical user interfaces and mapping rules, which convert the device specific representation of input and output description to a common representation language. - The implementation of a runtime platform that provides a flexible and extendable architecture for the easy integration of new devices and components. The platform realises concepts and strategies of multimodal human-computer interaction and is the basis for full-fledged multimodal dialogue applications for arbitrary device setups, domains, and scenarios. - A software development toolkit that is integrated in the Eclipse rich client platform and provides wizards and editors for creating and editing new multimodal dialogue applications.Cyber-physische Umgebungen (CPEs) erweitern natürliche Alltagsumgebungen wie Heim, Fabrik, Büro und Auto durch Verbindung der kybernetischen Welt der Computer und Kommunikation mit der realen, physischen Welt. Die möglichen Anwendungsgebiete hierbei sind weitreichend. Während unter dem Stichwort Industrie 4.0 cyber-physische Umgebungen eine bedeutende Rolle für die nächste industrielle Revolution spielen werden, erhalten sie ebenfalls Einzug in Heim, Büro, Werkstatt und zahlreiche weitere Bereiche. In solch einer neuen Welt geraten klassische Interaktionskonzepte, in denen Benutzer ausschließlich mit einem einzigen Gerät, PC oder Smartphone interagieren, immer weiter in den Hintergrund und machen Platz für eine neue Ausprägung der Interaktion zwischen dem Menschen und der Umgebung selbst. Darüber hinaus sorgen neue Technologien und ein wachsendes Spektrum an einsetzbaren Modalitäten dafür, dass sich im Interaktionsdesign neue Möglichkeiten für eine natürlichere und intuitivere verbale und nonverbale Kommunikation auftun. Die dynamische Natur von cyber-physischen Umgebungen und die Mobilität der Benutzer darin stellt Anwendungsentwickler vor die Herausforderung, Systeme zu entwickeln, die flexibel bezüglich der verbundenen und verwendeten Geräte und Modalitäten sind. Dies impliziert auch neue Möglichkeiten in der modalitätsübergreifenden Kommunikation, die über duale Interaktionskonzepte, wie sie heutzutage bereits üblich sind, hinausgehen. Die vorliegende Arbeit befasst sich mit der Unterstützung von Anwendungsentwicklern mit Hilfe einer Plattform zur deklarativen und modellbasierten Entwicklung von multimodalen Dialogapplikationen mit einem Fokus auf verteilte Ein- und Ausgabegeräte in cyber-physischen Umgebungen. Die bearbeiteten Aufgaben können grundlegend in drei Teile gegliedert werden: - Die Konzeption von Modellen und Strategien für die Spezifikation von Dialoganwendungen in einem deklarativen Entwicklungsansatz. Dies beinhaltet Modelle für das Definieren von Projektressourcen, Dialogverhalten, Spracherkennergrammatiken, graphischen Benutzerschnittstellen und Abbildungsregeln, die die gerätespezifische Darstellung von Ein- und Ausgabegeräten in eine gemeinsame Repräsentationssprache transformieren. - Die Implementierung einer Laufzeitumgebung, die eine flexible und erweiterbare Architektur für die einfache Integration neuer Geräte und Komponenten bietet. Die Plattform realisiert Konzepte und Strategien der multimodalen Mensch-Maschine-Interaktion und ist die Basis vollwertiger multimodaler Dialoganwendungen für beliebige Domänen, Szenarien und Gerätekonfigurationen. - Eine Softwareentwicklungsumgebung, die in die Eclipse Rich Client Plattform integriert ist und Entwicklern Assistenten und Editoren an die Hand gibt, die das Erstellen und Editieren von neuen multimodalen Dialoganwendungen unterstützen

Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates

The Perception of Emotion from Acoustic Cues in Natural Speech

Knowledge of human perception of emotional speech is imperative for the development of emotion in speech recognition systems and emotional speech synthesis. Owing to the fact that there is a growing trend towards research on spontaneous, real-life data, the aim of the present thesis is to examine human perception of emotion in naturalistic speech. Although there are many available emotional speech corpora, most contain simulated expressions. Therefore, there remains a compelling need to obtain naturalistic speech corpora that are appropriate and freely available for research. In that regard, our initial aim was to acquire suitable naturalistic material and examine its emotional content based on listener perceptions. A web-based listening tool was developed to accumulate ratings based on large-scale listening groups. The emotional content present in the speech material was demonstrated by performing perception tests on conveyed levels of Activation and Evaluation. As a result, labels were determined that signified the emotional content, and thus contribute to the construction of a naturalistic emotional speech corpus. In line with the literature, the ratings obtained from the perception tests suggested that Evaluation (or hedonic valence) is not identified as reliably as Activation is. Emotional valence can be conveyed through both semantic and prosodic information, for which the meaning of one may serve to facilitate, modify, or conflict with the meaning of the other—particularly with naturalistic speech. The subsequent experiments aimed to investigate this concept by comparing ratings from perception tests of non-verbal speech with verbal speech. The method used to render non-verbal speech was low-pass filtering, and for this, suitable filtering conditions were determined by carrying out preliminary perception tests. The results suggested that nonverbal naturalistic speech provides sufficiently discernible levels of Activation and Evaluation. It appears that the perception of Activation and Evaluation is affected by low-pass filtering, but that the effect is relatively small. Moreover, the results suggest that there is a similar trend in agreement levels between verbal and non-verbal speech. To date it still remains difficult to determine unique acoustical patterns for hedonic valence of emotion, which may be due to inadequate labels or the incorrect selection of acoustic parameters. This study has implications for the labelling of emotional speech data and the determination of salient acoustic correlates of emotion