Intention model based multi-round dialogue strategies for conversational AI bots

Tian, Junrui; Tu, Zhiying; Li, Nan; Su, Tonghua; Xu, Xiaofei; Wang, Zhongjie

doi:10.1007/s10489-022-03288-8

Cited by 7 publications

(1 citation statement)

References 28 publications

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“…To deal with these problems, some other researchers have presented their solutions. Multi-round dialogue strategies were designed by Tian et al [ 39 ] to induce users to express their needs, which effectively improved voice interaction and recognition to a certain extent. From another perspective, Werner et al [ 9 ] considered the participant characteristics when studying the interaction of older adults.…”

Section: Related Workmentioning

confidence: 99%

A multimodal domestic service robot interaction system for people with declined abilities to express themselves

Qin

Song

Wei

et al. 2023

Intel Serv Robotics

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Driven by the shortage of qualified nurses and the increasing average age of the population, the ambient assisted living style using intelligent service robots and smart home systems has become an excellent choice to free up caregiver time and energy and provide users with a sense of independence. However, users’ unique environments and differences in abilities to express themselves through different interaction modalities make intention recognition and interaction between user and service system very difficult, limiting the use of these new nursing technologies. This paper presents a multimodal domestic service robot interaction system and proposes a multimodal fusion algorithm for intention recognition to deal with these problems. The impacts of short-term and long-term changes were taken into account. Implemented interaction modalities include touch, voice, myoelectricity gesture, visual gesture, and haptics. Users could freely choose one or more modalities through which to express themselves. Virtual games and virtual activities of independent living were designed for pre-training and evaluating users’ abilities to use different interaction modalities in their unique environments. A domestic service robot interaction system was built, on which a set of experiments were carried out to test the system’s stability and intention recognition ability in different scenarios. The experiment results show that the system is stable and effective and can adapt to different scenarios. In addition, the intention recognition rate in the experiments was 93.62%. Older adults could master the system quickly and use it to provide some assistance for their independent living.

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Section: Related Workmentioning

confidence: 99%