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Linguistic Primitives: A New Model for Language Development in Robotics

机译:语言原语:机器人中语言开发的新模型

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Often in robotics natural language processing is used simply to improve the human-machine interaction. However, language is not only a powerful communication tool: it is deeply linked to the inner organization of the mind, and it guides its development. The aim of this paper is to take a first step towards a model of language which can be integrated with the diverse abilities of the robot, thus leading to its cognitive development, and eventually speeding up its learning capacity. To this end we propose and implement the Language Primitives Model (LPM) to imitate babbling, a phase in the learning process that characterizes a few months old babies. LPM is based on the same principles dictated by the Motor Primitives model. The obtained results positively compare with experimental data and observations about children, so confirming this interest of the new model.
机译:通常,在机器人中,自然语言处理仅用于提高人机交互。但是,语言不仅是一个强大的通信工具:它与心灵的内部组织密切相关,并指导其发展。本文的目的是迈向一种语言模型的第一步,可以与机器人的不同能力集成,从而导致其认知发展,并最终加速其学习能力。为此,我们提出并实施了语言原语模型(LPM)来模仿Babbling,一个阶段在学习过程中表征了几个月大的婴儿。 LPM基于运动基元模型决定的相同原理。所获得的结果与对儿童的实验数据和观察结果正面比较,因此证实了新模型的兴趣。

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