RESUMEN
Emotions play an important role in human-computer interaction, but there is limited research on affective and emotional virtual agent design in the area of teaching simulations for healthcare provision. The purpose of this work is twofold: firstly, to describe the process for designing affective intelligent agents that are engaged in automated communications such as person to computer conversations, and secondly to test a bespoke prototype digital intervention which implements such agents. The presented study tests two distinct virtual learning environments, one of which was enhanced with affective virtual patients, with nine 3rd year nursing students specialising in mental health, during their professional practice stage. All (100%) of the participants reported that, when using the enhanced scenario, they experienced a more realistic representation of carer/patient interaction; better recognition of the patients' feelings; recognition and assessment of emotions; a better realisation of how feelings can affect patients' emotional state and how they could better empathise with the patients.
RESUMEN
Our work provides a novel method for rich information discovery about the evolution of technical fields and company developments through patent relationships. A new exploratory method and graphical tool to discover technology proximity based on patent classification information are introduced. By technology we mean a technical field (defined by an International Patent Classification-IPC-code or a combination of them) or an organization (such as a tech company, research center, or institution). A single data structure is used for characterizing both technical fields and organizations, to visualize them as items of the very same body. This new method generates two graphs: the first graph, the TechnologyMap, visualizes technology items in a 2D plot wherein technical fields and companies will appear positioned relative to each other; the. A second graph, the Focused TechnologyMap, visualizes technology items with respect to a selected one, the focus, which is located in the center of a circle whose radii correspond to the complete set of IPC codes. This article represents the process and algorithms used for production of the graphs, and solidifies the assumptions of validity by presenting two of the many successful test cases to which it was applied.
RESUMEN
In recent years, rapid advancements have taken place for automatic speech recognition (ASR) systems and devices. Though ASR technologies have increased, the accessibility of these novel interaction systems is underreported and may present difficulties for people with speech impediments. In this article, we attempt to identify gaps in current research on the interaction between people with dysarthria and ASR systems and devices. We cover the period from 2011, when Siri (the first and the leading commercial voice assistant) was launched, to 2020. The review employs an interaction framework in which each element (user, input, system, and output) contributes to the interaction process. To select the articles for review, we conducted a search of scientific databases and academic journals. A total of 36 studies met the inclusion criteria, which included use of the word error rate (WER) as a measurement for evaluating ASR systems. This review determines that challenges in interacting with ASR systems persist even in light of the most recent commercial technologies. Further, understanding of the entire interaction process remains limited; thus, to improve this interaction, the recent progress of ASR systems must be elucidated.