1,720,963 research outputs found
A Cloud System for Diversity-Aware, Situated, Multi-Party Autonomous Interaction Between Humans and Robots
No full textThis PhD thesis focuses on the development of a cloud system designed for facilitating diversity-aware, situated, multi-party autonomous interactions between humans and artificial agents. The objective is to empower robots to actively engage in conversations, adapting to individual needs and preferences, and mimicking behaviors commonly observed in interactions among multiple humans. The specific functionalities include speaker recognition, conversation state and user statistics monitoring, and, when required, assuming the role of a moderator.
To achieve this goal, the Cloud Artificial Intelligence and Robotics (CAIR) system has been developed, using an ontology for knowledge-based autonomous interaction between conversational agents and humans. This design allows for flexibility and expansion by incorporating new services to enhance the capabilities of connected clients. To empower robots with the ability to interact with groups of people, a speaker recognition mechanism has been implemented. The data collected during conversations have been used to develop several control policies, determining which speaker to address and controlling the dynamics of the conversation.
The system is equipped with the ability to adapt to diverse populations and individuals according to the concept of “diversity-awareness,'' encompassing factors like background, personality, age, gender, and culture. To achieve a diversity-aware conversation, the initial step involved modifying the ontology by adjusting the probabilities of certain conversation topics and refining sentences to mitigate potential discomfort. Subsequently, the integration of large language models (LLMs) into the system facilitated the realization of a diversity-aware conversation. This was achieved by providing the model with comprehensive information about users, the conversation's history, contextual details, and specific guidelines for generating responses. To enhance diversity-awareness in responses, a pioneering approach involved endowing robots with the ability to perceive and interpret visual surroundings through textual descriptions. It is essential to emphasize that LLMs were used as a tool, with the conversation flow remaining anchored in the structure of the system's pre-established ontology.
Preliminary experiments were conducted to evaluate the CAIR cloud server's ability to handle numerous simultaneous requests while maintaining a low response time. The results of these experiments formed the basis for appropriately sizing the system, presenting a sustainable solution for both verbal and non-verbal interactions with low-cost robots and other smart devices.
The multi-party capabilities of the CAIR system were assessed through experiments in a middle school involving 300 participants grouped into fours. In these experiments, the robot assumed the role of a moderator, implementing different policies. The results indicated effective control of group conversation dynamics in terms of balancing user participation and reducing the number of subgroups. Notably, participants reported positive interaction experiences regardless of the control policy employed.
To evaluate the impact of a diversity-aware system, experiments were conducted in a hospital setting with 10 clinicians and 10 individuals with spinal cord injuries (SCI). The system’s knowledge base was carefully adapted to people with SCI with the help of healthcare staff. The findings supported the necessity of using diversity-aware robots, showing that people with SCI reported lower anxiety and higher enjoyment levels than clinicians. Additionally, the users' perception of the robot remained consistent in longer interactions, demonstrating sustained effectiveness despite reduced novelty.
After integrating LLMs into the system, experiments were carried out to evaluate the system's performance in real-world scenarios and measure various performance indicators. The findings confirmed the effectiveness of the implemented system, facilitating diversity-aware conversations that leverage the strengths of a tailored knowledge base along with powerful tools like LLMs and techniques for extracting data from visual information.
Clients for the CAIR cloud have been developed for a variety of devices, including computers, Android smartphones, Aldebaran robots NAO and Pepper, the Einstein robot by Hanson Robotics, and the AlterEgo robot designed by the Italian Institute of Technology (IIT). This showcases the ease of connecting devices to CAIR and leveraging its capabilities. The system's adaptability extends to diverse contexts, such as education, healthcare, retail, fairs, and homes. Its versatility enables it to provide companionship, support individuals with specific needs, enhance learning experiences in educational settings, and entertain groups of people in public contexts
Knowledge-driven conversation for social robots: Exploring crowdsourcing mechanisms for improving the system capabilities
No full textSocial robots and artificial agents should be able to interact with the user in the most natural way possible. This
work describes the basic principles of a conversation system designed for social robots and artificial agents,
which relies on knowledge encoded in the form of an Ontology. Given the knowledge-driven approach, the
possibility of expanding the Ontology in run-time, during the verbal interaction with the users is of the utmost importance: this paper also deals with the implementation of a system for the run-time expansion of the
knowledge base, thanks to a crowdsourcing approach
Cloud Services for Social Robots and Artificial Agents
No full textThis work presents the design and the implementation of CAIR: a cloud system for knowledge-based interaction devised for Social Robots and other conversational agents. The system is structured in a way that it can be easily expanded by adding new services that improve the capabilities of the clients connected to the Cloud. Another key feature of the system is that it has been designed to make the development of its clients straightforward: in this way, multiple devices (e.g., robots, computers, smartphones, etc.) can be easily endowed with the capability of autonomously interacting with the user, understanding when to perform specific actions, and exploiting all the information provided by services on the Cloud
Physical Embodiment of Conversational Social Robots
No full textAchieving natural and engaging verbal interactions is one of the main challenges faced by Social Robotics. In this context, physical embodiment may be one of the most critical factors: indeed, previous work indicates that physical robots elicit more favorable social responses than virtual agents. However, the effects of physical embodiment have been analysed only in some specific and limited scenarios, where verbal interaction was reduced to basic commands.The current work aims at investigating the effect of robots' physical embodiment in a pure conversation task, by considering some relevant aspects of social interaction, such as usability, speech interface quality, user satisfaction and engagement. To this aim, a pilot experiment where participants were required to chitchat with a robot and a smartphone app, both connected to the same conversation framework, has been carried out. Preliminary results are presented and discussed, and they offer interesting insights about the positive effects of physical embodiment on some of the analysed aspects
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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