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... capabilities are achieved respectively: connecting to the Google Automatic Speech Recognition (ASR) Cloud using Google APIs for Android for speech-to-text conversion; using Onboard Language Processing as well as the CARESSES Cloud for speech understanding; using Google APIs for Android text-to-speech conversion. Figure 6 on the bottom depicts the general software architecture, which resembles the one used for the Pepper robot case study, without the need for an external PC. The Figure also shows that a different culture will entail not only different sentences from the Cloud but also Virtual Characters with different ethnicity and cultural heritage. ...
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Citations
... The robot's ability to converse autonomously with multiple people is enabled by CAIR (Cloud Artificial Intelligence and Robotics), a cloud software architecture specifically designed for autonomous conversation [17,10]. This system relies on a framework for knowledge representation, utilizing an ontology implemented in OWL2. ...
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.
... This demand is met using assistive and social robots [1]. The development of artificial intelligence techniques, particularly efficient audio processing in the computational cloud [2], enables the successful implementation of a voice communication interface as the primary HMI for this class of robots. ...
Social and assistive robotics have vastly increased in popularity in recent years. Due to the wide range of usage, robots executing such tasks must be highly reliable and possess enough functions to satisfy multiple scenarios. This article describes a mobile, artificial intelligence-driven, robotic platform Rico. Its prior usage in similar scenarios, the number of its capabilities, and the experiments it presented should qualify it as a proper arm-less platform for social and assistive circumstances.
... II. SYSTEM ARCHITECTURE The system presented in this paper is a modification of the CAIR (Cloud AI and Robotics) system described in [14]. CAIR is a cloud-based system for autonomous interaction built upon an OWL2 ontology for rich, knowledge-grounded conversations [15]. The ontology is designed to consider cultural differences between users in a non-stereotyped manner. ...
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.
... To represent the predictive model of the chatbot, we have chosen the ANN structure because it has achieved good results among different computational approaches used to develop chatbots [19]. In fact, to select our model structure (ANN), a search was conducted to explore various potential structures used in other chatbot solutions [19], [20], [21], [22]. Below, we present the key details of both the model's structure and its training process and subsequent evaluation. ...
Students at the University of Guayaquil who are pursuing a degree in Software Engineering and who have difficulty obtaining information about enrollment and tuition payments are the target audience of the application developed in this study. For this purpose, a chatbot is proposed. It uses machine learning (ML) and natural language processing (NLP) to answer students' questions. To evaluate the usability of the system from a quantitative point of view, the time taken by six students to complete user registration (T1), perform five searches (T2), and unsubscribe (T3) was measured in minutes, with an average duration of three minutes for each activity. To assess students' perceptions of the use of the proposed chatbot, a sample of sixty students who had previously interacted with the proposed solution were surveyed. Aspects evaluated included: Ease of use of the system (A), Speed (B), Appropriate behavior (C), Confidence to use it again (D), and Quality of the answer provided (E). Each of the evaluated features (A-E) was rated above 3 out of 5 in most cases. Thus, the chatbot solution is well accepted by the students, even considering its use in future academic semesters. INDEX TERMS Chatbot, cloud server, natural language processing, neural network, machine learning.
... It's important to note that constructing a specific architecture that links Pepper to OpenAI involves technical expertise in robotics, software development, and familiarity with the OpenAI platform. There are papers in the literature showing this complexity of software implementation (Recchuto et al., 2020;Grassi et al., 2021); in these articles a technical approach similar to that employed by the authors for the present work is adopted, as shown in technical section. They employ an API-like Cloud service queried using the GET request system. ...
Neurodevelopmental Disorders (NDDs) represent a significant healthcare and economic burden for families and society. Technology, including AI and digital technologies, offers potential solutions for the assessment, monitoring, and treatment of NDDs. However, further research is needed to determine the effectiveness, feasibility, and acceptability of these technologies in NDDs, and to address the challenges associated with their implementation. In this work, we present the application of social robotics using a Pepper robot connected to the OpenAI system (Chat-GPT) for real-time dialogue initiation with the robot. After describing the general architecture of the system, we present two possible simulated interaction scenarios of a subject with Autism Spectrum Disorder in two different situations. Limitations and future implementations are also provided to provide an overview of the potential developments of interconnected systems that could greatly contribute to technological advancements for Neurodevelopmental Disorders (NDD).
... These technologies enable intelligent decision-making, process optimization and enhanced data management, leading to improved efficiency and accuracy within HR operations. 7 The benefits of HR automation are numerous. It reduces manual errors, increases process efficiency and ensures data integrity. ...
Automation has become a game-changer in the field of Human Resource (HR), revolutionizing traditional HR operations and transforming the way organizations manage their workforce. This study explores the concept of automation in HR and its impact on various HR functions including recruitment, onboarding, employee data management, payroll administration, performance management and employee engagement. The study delves into the benefits of HR automation such as increased efficiency, improved accuracy, reduced manual errors and enhanced employee experiences. It highlights the different technologies and tools used for HR automation including Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML) and data analytics. Overall, automation in HR operations brings numerous benefits to organizations including improved efficiency, accuracy, compliance and employee satisfaction. HR professionals can focus on strategic initiatives and value-added tasks, resulting in better talent management and organizational success in the dynamic business landscape.
... And, World Health Organization (WHO) claims that fall-related injuries are common resulting in different complications [3], along with decreased quality of life and depression due to fear of falling [4] and is the second most significant reason for elderly death. Again, sighting this global increase of elderly population, [5] has claimed that the expected Compound Annual Growth Rate (CAGR) of assitive robots application will be more than 22% in the next couple of years. They have also claimed that the CAGR of healthcare assistive robots' market will increase to 36% by the end of 2024. ...
... Some desirable features that are not present in most systems are: (1) Breaking the "simple commands only" barrier; (2) Multiple speech acts; (3) 1 http://caressessrobot.org/. 2 CARESSES architecture has been recently revised to allow for a Cloud-based implementation [14], thus enabling virtually any device equipped with a network interface to perform long-term, culture-aware conversation with the user. Currently, the robots Pepper and NAO, the pill-dispenser Pillo, Prof. Einstein, and a virtual character implemented as an Android application have been provided with the onboard functionalities to implement the instructions received by the CARESSES Cloud [15]. Mixed initiative dialogue;(4) Situated language and the symbol grounding problem; (5) Affective interaction; (6) Motor correlates and Non-Verbal Communication; (7) Purposeful speech and planning; (8) Multi-level learning; (9) Utilization of online resources and services. ...
... 14 http://caressessrobot.org/IJSORO2021/. Figures 7,9,11,13,15,17,and 19, report the histograms representing the average and the standard deviation for each group respectively for the Coherence, Accuracy, Likeability, Cognitive Demand, Annoyance and Speed. Please notice that, in contrast with the other scales of the SASSI, a higher value of Cognitive Demand represents a negative aspect. ...
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 input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible , the user 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.
... Concerning the latter, a knowledge-based framework for culture-aware conversation has been developed: the system allows for letting the robot talk about a huge number of topics that may be more or less relevant for different cultures, by properly managing the flow of the conversation. The system, originally conceived for the humanoid robot Pepper, has been recently refactored as a portfolio of Cloud services [35,36]. ...
Embedding social robots with the capability of accompanying their sentences with natural gestures may be the key to increasing their acceptability and their usage in real contexts. However, the definition of natural communicative gestures may not be trivial, since it strictly depends on the culture of the person interacting with the robot. The proposed work investigates the possibility of generating culture-dependent communicative gestures, by proposing an integrated approach based on a custom dataset composed exclusively of persons belonging to the same culture, an adversarial generation module based on speech audio features, a voice conversion module to manage the multi-person dataset, and a 2D-to-3D mapping module for generating three-dimensional gestures. The approach has eventually been implemented and tested with the humanoid robot Pepper. Preliminary results, obtained through a statistical analysis of the evaluations made by human participants identifying themselves as belonging to different cultures, are discussed.
... Finally, we only examined work from HRI and T-HRI in the last five years. Whereas SAR research is published across a wide variety of venues [5], [2], [59], [60], [61], [62], [63]. ...
Socially Assistive Robots (SARs) show significant promise in a number of domains: providing support for the elderly, assisting in education, and aiding in therapy. Perhaps un-surprisingly, SAR research has traditionally focused on providing evidence for this potential. In this paper, we argue that this focus has led to a lack of critical reflection on the appropriate level of autonomy (LoA) for SARs, which has in turn led to blind spots in the research literature. Through an analysis of the past five years of HRI literature, we demonstrate that SAR researchers are overwhelmingly developing and envisioning autonomous robots. Critically, researchers do not include a rationale for their choice in LoA, making it difficult to determine their motivation for fully autonomous robots. We argue that defaulting to research fully autonomous robots is potentially shortsighted , as applying LoA selection guidelines to many SAR domains would seem to warrant levels of autonomy that are closer to teleoperation. We moreover argue that this is an especially critical oversight as teleoperated robots warrant different evaluation metrics than do autonomous robots since teleoperated robots introduce an additional user, the teleoperator. Taken together, this suggests a mismatch between LoA selection guidelines and the vision of SAR autonomy found in the literature. Based on this mismatch, we argue that the next five years of SAR research should be characterized by a shift in focus towards teleoperation and teleoperators.
