Toward a Conversation Partner Agent for People with Aphasia: Assisting Word Retrieval

Kuwabara, Kazuhiro; Iwamae, Takayuki; Wada, Yoshito; Huang, Hung-Hsuan; Takenaka, Keisuke

doi:10.1007/978-3-319-39630-9_17

Cited by 6 publications

(1 citation statement)

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“…Systems have been proposed that help aphasia sufferers recall an item's name (Arima, Kuroiwa, Horiuchi, & Furukawa, 2015;Kuwabara, Iwamae, Wada, Huang, & Takenaka, 2016). Such word-finding difficulty is one typical symptom of a person with aphasia who has a clear mental image of an item but cannot find its name or the language to express it.…”

Section: Word Retrieval Assistantmentioning

confidence: 99%

Tuning a conversation strategy for interactive recommendations in a chatbot setting

Ikemoto

Asawavetvutt

Kuwabara

et al. 2018

Journal of Information and Telecommunication

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This paper presents a conversation strategy for interactive recommendations using a chatbot. Chatbots have recently been attracting attention for their use as a flexible user interface. To develop an effective chatbot, it is important to determine what kind of questions to ask, what information should be provided, and how to process a user's responses for a given task. In this paper, we target a chatbot that uses a graphical user interface (GUI) and focus on the task of recommending an item that suits a user's preference. We propose a conversation strategy where a chatbot combines questions about a user's preferences and recommendations while soliciting user's feedback to them. The balance between the questions and recommendations is controlled by changing the parameter values. In addition, we propose a simulation model to evaluate the performance of interactive recommendation under different parameter values. The simulation results with a prototype dataset are presented and discussed.

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Section: Word Retrieval Assistantmentioning

confidence: 99%