The role of spoken language dialogue interaction in intelligent environments

Minker, Wolfgang; López-Cózar, Ramón; McTear, Michael F.

doi:10.3233/ais-2009-0004

Cited by 23 publications

(15 citation statements)

References 11 publications

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“…The role of emotion recognition in natural dialogue between humor and computers was emphasized by many scientists, e.g. Minker et al [20]. Research on computers using and understanding humor may not yet be highly popular, but continues to gather more and more scientific attention (see Section 1.3).…”

Section: Introductionmentioning

confidence: 99%

Multiagent system for joke generation: Humor and emotions combined in human-agent conversation

Dybała¹,

Ptaszyński²,

Maciejewski³

et al. 2010

Journal of Ambient Intelligence and Smart Environments

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In this paper we present an innovative work on a multiagent joking conversational system. In our research so far we have shown that implementing humor into a chatterbot can visibly improve its performance. The results presented in this paper are the outcome of the next step of our work. They show that a multiagent system, combining a conversational agent, a pun generator and an emotiveness analysis engine, works reasonably well in interactions with users. In the setup used in this research, the emotiveness analysis agent analyses users' utterances and decides whether it is appropriate to tell a pun. Depending on the results of this analysis, the agent chooses either the pun generator, if the decision is that a joke should be told, or the non-humor-equipped agent when the decision is different. Two evaluation experiments were conducted: user (first person) focused and automatic (emotiveness-analysis-based). In both, we compared the performance of the multiagent joking system and a baseline (non-humorous) conversation agent. The results show that in both cases the humor-equipped engine was evaluated as better than the baseline agent. The results are discussed and some ideas for the future are given.

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Section: Introductionmentioning

confidence: 99%

Multiagent system for joke generation: Humor and emotions combined in human-agent conversation

Dybała¹,

Ptaszyński²,

Maciejewski³

et al. 2010

Journal of Ambient Intelligence and Smart Environments

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“…Smart environments have an increased awareness of the users' habits through IoT by integrating new interconnected home appliances [20,21,22]. All these devices transparently obtain pertinent information that can complement the knowledge that is extracted from natural language through direct explicit interaction with the user [23].…”

Section: Related Workmentioning

confidence: 99%

Architecting dietary intake monitoring as a service combining NLP and IoT

Benítez-Guijarro

Callejas

Noguera

et al. 2019

J Ambient Intell Human Comput

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Currently there exist many tools that support monitoring and encouragement of healthy nutrition habits in the context of wellness promotion. In this domain, interfaces based on natural language provide more flexibility for nutritional self-reporting than traditional form-based applications, allowing the users to provide richer and spontaneous descriptions. Nonetheless, in certain circumstances, natural language records may miss some important aspects, such as the quantity of food eaten, which results in incomplete recordings. In the Internet-of-Things (IoT) paradigm, smart home appliances can support and complement the recording process so as to make it more accurate. However, in order to build systems that support the semantic analysis of nutritional self-reports, it is necessary to integrate multiple inter-related components, possibly within complex e-health platforms. For this reason, these components should be designed and encapsulated avoiding monolithic approaches that derive in rigidity and dependency of particular technologies. Currently, there are no models or architectures that serve as a reference for developers towards this objective. In this paper, we present a service-based architecture that helps to contrast and complement the descriptions of food intakes by means of connected smart home devices, coordinating all the stages during the process of recognizing food records provided in natural language. Additionally, we aim to identify and design the essential services that are required to automate the recording and subsequent processing of natural language descriptions of nutritional intakes in association with smart home devices. The functionalities provided by each of these services are ready to work in isolation, just out of the box, or in downstream pipeline processes, bypassing the inconveniences of monolithic architectures.

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“…In a culturally aware intelligent conversation agent, the Dialogue Management (DM) sitting at the core of a dialogue system (Minker et al, 2009) has to be aware of cultural interaction idiosyncrasies to generate culturally appropriate output. Hence, the DM is not only responsible for what is said next, but also for how it is said.…”

Section: Integrating Cultural Idiosyncrasiesmentioning

confidence: 99%

Cultural Communication Idiosyncrasies in Human-Computer Interaction

Miehle

Yoshino

Pragst

et al. 2016

Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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In this work, we investigate whether the cultural idiosyncrasies found in humanhuman interaction may be transferred to human-computer interaction. With the aim of designing a culture-sensitive dialogue system, we designed a user study creating a dialogue in a domain that has the potential capacity to reveal cultural differences. The dialogue contains different options for the system output according to cultural differences. We conducted a survey among Germans and Japanese to investigate whether the supposed differences may be applied in human-computer interaction. Our results show that there are indeed differences, but not all results are consistent with the cultural models.

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The role of spoken language dialogue interaction in intelligent environments

Cited by 23 publications

References 11 publications

Multiagent system for joke generation: Humor and emotions combined in human-agent conversation

Multiagent system for joke generation: Humor and emotions combined in human-agent conversation

Architecting dietary intake monitoring as a service combining NLP and IoT

Cultural Communication Idiosyncrasies in Human-Computer Interaction

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