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Can a Virtual Human Facilitate Language Learning in a Young Baby?

Setareh Nasihati Gilani, David Traum, Rachel Sortino, Grady Gallagher, Kailyn Aaron-Lozano, Cryss Padilla, Ari Shapiro, Jason Lamberton, Laura‐Ann Petitto

Year
2019
Citations
3

Abstract

There is a significant paucity of work on language learning systems for young infants [2, 5, 19] despite the widely understood critical importance that this developmental period has for healthy language and cognitive growth, and related reading and academic success [6, 14]. Deaf babies constitute one vulnerable population as they can experience dramatically reduced or no access to usable linguistic input during this period [18]. This causes potentially devastating impact on children's linguistic, cognitive, and social skills [9, 10, 15, 16, 20]. We introduced an AI system, called RAVE (Robot, AVatar, thermal Enhanced language learning tool), designed specifically for babies within the age range of 6-12 months [8, 17]. RAVE consists of two agents: a virtual human (provides language and socially contingent interactions) and an embodied robot (provides socially engaging physical cues to babies and directs babies' attention to the virtual human). Detailed description of the system's constituent components and dialogue algorithms are presented in [17] and [8].

Keywords

AvatarLanguage acquisitionEmbodied cognitionReading (process)Computer scienceCognitionVirtual actorPsychologyUSablePopulation

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