Carmine Tommaso Recchiuto

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

This research investigates the impact of social robot participation in group conversations and assesses the effectiveness of various addressing policies. The study involved 300 participants, divided into groups of four, interacting with a humanoid robot serving as the moderator. The robot utilized conversation data to determine the most appropriate speaker to address. The findings indicate that the robot's addressing policy significantly influenced conversation dynamics, resulting in more balanced attention to each participant and a reduction in subgroup formation.

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

This paper presents a system for diversity-aware autonomous conversation leveraging the capabilities of large language models (LLMs). The system adapts to diverse populations and individuals, considering factors like background, personality, age, gender, and culture. The conversation flow is guided by the structure of the system's pre-established knowledge base, while LLMs are tasked with various functions, including generating diversity-aware sentences. Achieving diversity-awareness involves providing carefully crafted prompts to the models, incorporating comprehensive information about users, conversation history, contextual details, and specific guidelines. To assess the system's performance, we conducted both controlled and real-world experiments, measuring a wide range of performance indicators.

Luca Morando, Carmine Tommaso Recchiuto, Jacopo Callà et al.

Since photovoltaic (PV) plants require periodic maintenance, using Unmanned Aerial Vehicles (UAV) for inspections can help reduce costs. The thermal and visual inspection of PV installations is currently based on UAV photogrammetry. A UAV equipped with a Global Positioning System (GPS) receiver is assigned a flight zone: the UAV will cover it back and forth to collect images to be later composed in an orthomosaic. The UAV typically flies at a height above the ground that is appropriate to ensure that images overlap even in the presence of GPS positioning errors. However, this approach has two limitations. Firstly, it requires to cover the whole flight zone, including "empty" areas between PV module rows. Secondly, flying high above the ground limits the resolution of the images to be later inspected. The article proposes a novel approach using an autonomous UAV equipped with an RGB and a thermal camera for PV module tracking. The UAV moves along PV module rows at a lower height than usual and inspects them back and forth in a boustrophedon way by ignoring "empty" areas with no PV modules. Experimental tests performed in simulation and an actual PV plant are reported.

Giulia Zaino, Carmine Tommaso Recchiuto, Antonio Sgorbissa

The article introduces the concept of image "culturization," which we define as the process of altering the ``brushstroke of cultural features" that make objects perceived as belonging to a given culture while preserving their functionalities. First, we defined a pipeline for translating objects' images from a source to a target cultural domain based on state-of-the-art Generative Adversarial Networks. Then, we gathered data through an online questionnaire to test four hypotheses concerning the impact of images belonging to different cultural domains on Italian participants. As expected, results depend on individual tastes and preferences: however, they align with our conjecture that some people, during the interaction with an intelligent system, will prefer to be shown images modified to match their cultural background. The study has two main limitations. First, we focussed on the culturization of individual objects instead of complete scenes. However, objects play a crucial role in conveying cultural meanings and can strongly influence how an image is perceived within a specific cultural context. Understanding and addressing object-level translation is a vital step toward achieving more comprehensive scene-level translation in future research. Second, we performed experiments with Italian participants only. We think that there are unique aspects of Italian culture that make it an interesting and relevant case study for exploring the impact of image culturization. Italy is a very culturally conservative society, and Italians have specific sensitivities and expectations regarding the accurate representation of their cultural identity and traditions, which can shape individuals' preferences and inclinations toward certain visual styles, aesthetics, and design choices. As a consequence, we think they are an ideal candidate for a preliminary investigation of image culturization.

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user's input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user's intention to drive the conversation in specific directions while avoiding purely reactive responses to what the user says. To measure the quality of the conversation, the article reports the tests performed with 100 recruited participants, comparing five conversational agents: (i) an agent addressing dialogue flow management based only on the detection of keywords in the speech, (ii) an agent based both on the detection of keywords and the Content Classification feature of Google Cloud Natural Language, (iii) an agent that picks conversation topics randomly, (iv) a human pretending to be a chatbot, and (v) one of the most famous chatbots worldwide: Replika. The subjective perception of the participants is measured both with the SASSI (Subjective Assessment of Speech System Interfaces) tool, as well as with a custom survey for measuring the subjective perception of coherence.

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

This article describes a novel approach to expand in run-time the knowledge base of an Artificial Conversational Agent. A technique for automatic knowledge extraction from the user's sentence and four methods to insert the new acquired concepts in the knowledge base have been developed and integrated into a system that has already been tested for knowledge-based conversation between a social humanoid robot and residents of care homes. The run-time addition of new knowledge allows overcoming some limitations that affect most robots and chatbots: the incapability of engaging the user for a long time due to the restricted number of conversation topics. The insertion in the knowledge base of new concepts recognized in the user's sentence is expected to result in a wider range of topics that can be covered during an interaction, making the conversation less repetitive. Two experiments are presented to assess the performance of the knowledge extraction technique, and the efficiency of the developed insertion methods when adding several concepts in the Ontology.