CLARA: A Multifunctional Virtual Agent for Conference Support and Touristic Information

D’Haro, Luis Fernando; Kim, Seokhwan; Yeo, Kheng Hui; Jiang, Ridong; Niculescu, Andreea I.; Banchs, Rafael E.; Li, Haizhou

doi:10.1007/978-3-319-19291-8_22

Cited by 15 publications

(12 citation statements)

References 6 publications

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“…For instance, Niculescu et al developed SARA (Singapore's Automated Responsive Assistant), a robotic virtual agent, to offer information and assistance to tourists, being able to detect the user's location on a map [48]. CLARA is a virtual restaurant recommendation system and conversational agent that provides tourists with information about sightseeing, restaurants, transportation, and general information about Singapore [49]. However, the adoption of service robots inevitably changes the nature of service experience.…”

Section: The Importance Of Facilitating Human-robot Interactionmentioning

confidence: 99%

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

et al. 2020

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Over recent years, robots are increasingly being employed in several aspects of modern society. Among others, social robots have the potential to benefit education, healthcare, and tourism. To achieve this purpose, robots should be able to engage humans, recognize users’ emotions, and to some extent properly react and "behave" in a natural interaction. Most robotics applications primarily use visual information for emotion recognition, which is often based on facial expressions. However, the display of emotional states through facial expression is inherently a voluntary controlled process that is typical of human–human interaction. In fact, humans have not yet learned to use this channel when communicating with a robotic technology. Hence, there is an urgent need to exploit emotion information channels not directly controlled by humans, such as those that can be ascribed to physiological modulations. Thermal infrared imaging-based affective computing has the potential to be the solution to such an issue. It is a validated technology that allows the non-obtrusive monitoring of physiological parameters and from which it might be possible to infer affective states. This review is aimed to outline the advantages and the current research challenges of thermal imaging-based affective computing for human–robot interaction.

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Section: The Importance Of Facilitating Human-robot Interactionmentioning

confidence: 99%

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

et al. 2020

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“…Recently researchers tend to evaluate their methodological improvements relative to a sequence-to-sequence (Seq2Seq) baseline (Sutskever et al, 2014), as proposed for utterance generation by Shang et al (2015); Vinyals and Le (2015); as well to compare against each other. While crowd-sourcing experiments are relatively cheap, the lack of automatic metrics means that every change in model architecture requires new evaluations.…”

Section: Chatbot Evaluationmentioning

confidence: 99%

“…We conducted a series of experiments to establish high-quality baselines for several popular training sets to show the efficacy of our proposed method. We compared our baselines against the OpenNMT benchmark for dialog systems 4 ; Cakechat 5 , which is a reimplementation of the hierarchical encoderdecoder model (HRED) ; and the Neural Conversation Model's (NCM) released responses from Vinyals and Le (2015). Cakechat was trained on Twitter data, and NCM and Open-NMT benchmark were trained on movie subtitle data from OpenSubtitles (Tiedemann, 2012).…”

Section: System Descriptionsmentioning

confidence: 99%

“…Our evaluation set is the list of 200 questions released by Vinyals and Le (2015) in their seminal work on neural conversational models using a standard Seq2Seq framework borrowed from machine translation. The evaluation set is handcrafted and there are several correlated examples, such as the prompts are you a follower or a leader ?…”

Section: Selection Of Evaluation Setmentioning

confidence: 99%

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Item Response Theory for Efficient Human Evaluation of Chatbots

Sedoc¹,

Ungar²

2020

Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems

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Conversational agent quality is currently assessed using human evaluation, and often requires an exorbitant number of comparisons to achieve statistical significance. In this paper, we introduce Item Response Theory (IRT) for chatbot evaluation, using a paired comparison in which annotators judge which system responds better to the next turn of a conversation. IRT is widely used in educational testing for simultaneously assessing the ability of test takers and the quality of test questions. It is similarly well suited for chatbot evaluation since it allows the assessment of both models and the prompts used to evaluate them. We use IRT to efficiently assess chatbots, and show that different examples from the evaluation set are better suited for comparing highquality (nearer to human performance) than low-quality systems. Finally, we use IRT to reduce the number of evaluation examples assessed by human annotators while retaining discriminative power.

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“…It is considered the first "chatbot", a text-based conversational agent simulating a natural human interaction between the computer and a user. Recently, conversational agents have been created for the touristic [37] and customer service domain [38], or in social networks like Facebook or Twitter [39]. Additionally, agents have found wide-spread applications in healthcare applications and clinical psychology, as indicated by recent reviews from Laranjo et al [40], Montenegro et al [41], or Provoost et al [42].…”

Section: Related Workmentioning

confidence: 99%

Exploring Smart Agents for the Interaction with Multimodal Mediated Environments

Richer

Zhao

Eskofier

et al. 2020

MTI

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After conversational agents have been made available to the broader public, we speculate that applying them as a mediator for adaptive environments reduces control complexity and increases user experience by providing a more natural interaction. We implemented and tested four agents, each of them differing in their system intelligence and input modality, as personal assistants for Mediated Atmospheres, an adaptive smart office prototype. They were evaluated in a user study ( N = 33 ) to collect subjective and objective measures. Results showed that a smartphone application was the most favorable system, followed by conversational text and voice agents that were perceived as being more engaging and intelligent than a non-conversational voice agent. Significant differences were observed between native and non-native speakers in both subjective and objective measures. Our findings reveal the potential of conversational agents for the interaction with adaptive environments to reduce work and information overload.

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CLARA: A Multifunctional Virtual Agent for Conference Support and Touristic Information

Cited by 15 publications

References 6 publications

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

Item Response Theory for Efficient Human Evaluation of Chatbots

Exploring Smart Agents for the Interaction with Multimodal Mediated Environments

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