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Mutual belief forming by robots based on the process of utterance comprehension

机译:基于话语理解过程的机器人互信形成

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摘要

This paper describes a method of learning a mutual belief, necessary for natural language communication with people, in a process of utterance comprehension by robot. In this method, a system of mutual beliefs is represented by multiple beliefs, and the weights for the confidence that each of the belief is shared with a human. The beliefs dealt with in the method include phonemes, lexicon, grammar, influence of behavioral context, and other nonlinguistic belie* In the experiment, arm-robot with only a basic language knowledge interacts with human by using language and action. Through the interaction, robot learned the mutual beliefs and was eventually able to understand even fragmental and ambiguous utterances according to given situations, and act appropriately. The methods made it possible to integrate the language and cognitive processes, and thus introducing a new framework for natural communication.
机译:本文介绍了一种在机器人的发声理解过程中学习与人进行自然语言交流所必需的共同信念的方法。在这种方法中,互信系统由多个信念表示,权重为每个信念与人类共享的信心。该方法处理的信念包括音素,词典,语法,行为情境的影响和其他非语言掩饰*。在实验中,仅具有基本语言知识的机器人通过使用语言和动作与人互动。通过互动,机器人学会了相互的信念,并最终能够根据给定的情况理解甚至是零散和模棱两可的话语,并采取适当的行动。这些方法使整合语言和认知过程成为可能,从而为自然交流引入了新的框架。

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