Detecting robot-directed speech by situated understanding in object manipulation tasks

Zuo, Xiang; Iwahashi, Naoto; Taguchi, Ryo; Funakoshi, Kotaro; Nakano, Mikio; Matsuda, Shigeki; Sugiura, Komei; Oka, Naoki

doi:10.1109/roman.2010.5598729

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Research has applied speech-based approaches to deploy robotic systems in a wide variety of environments. For example, these approaches have been used in manipulators [7,8,9], aerial vehicles [10], and wheeled platforms [11,12]. Moreover, several prototypes have been developed for social robots carrying out specialized tasks, such as attending as a waiter [13], as a receptionist [15] or as a bartender [14].…”

Section: Related Workmentioning

confidence: 99%

Language-Based Sensing Descriptors for Robot Object Grounding

Gemignani

Veloso

Nardi

2015

RoboCup 2015: Robot World Cup XIX

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In this work, we consider an autonomous robot that is required to understand commands given by a human through natural language. Specifically, we assume that this robot is provided with an internal representation of the environment. However, such a representation is unknown to the user. In this context, we address the problem of allowing a human to understand the robot internal representation through dialog. To this end, we introduce the concept of sensing descriptors. Such representations are used by the robot to recognize unknown object properties in the given commands and warn the user about them. Additionally, we show how these properties can be learned over time by leveraging past interactions in order to enhance the grounding capabilities of the robot.

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Section: Related Workmentioning

confidence: 99%

Language-Based Sensing Descriptors for Robot Object Grounding

Gemignani

Veloso

Nardi

2015

RoboCup 2015: Robot World Cup XIX

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“…The robotic system is truthfully an embodied natural language processing system that can take various contexts that an ordinal amodal natural processing system cannot access. Zuo et al applied this model for detecting robot-directed speech [134]. Sugiura et al proposed a method for estimating the ambiguity in commands by introducing an active learning scheme to the conversation system, based on the mutual belief [135].…”

Section: Mutual Belief Systemmentioning

confidence: 99%

Symbol Emergence in Robotics: A Survey

Taniguchi

Nagai

Nagaoka

et al. 2015

Preprint

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Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially selforganized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-ofart research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory-motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.

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Knowledgeable Talking Robots

Aiello

Bastianelli

Iocchi

et al. 2013

Artificial General Intelligence

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Speech technologies nowadays available on mobile devices show an increased performance both in terms of the language that they are able to capture and in terms of reliability. The availability of performant speech recognition engines suggests the deployment of vocal interfaces also in consumer robots. In this paper, we report on our current work, by specifically focussing on the difficulties that arise in grounding the user's utterances in the environment where the robot is operating. © 2013 Springer-Verlag

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Detecting robot-directed speech by situated understanding in object manipulation tasks

Cited by 4 publications

References 12 publications

Language-Based Sensing Descriptors for Robot Object Grounding

Language-Based Sensing Descriptors for Robot Object Grounding

Symbol Emergence in Robotics: A Survey

Knowledgeable Talking Robots

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