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Unsupervised Multimodal Word Discovery based on Double Articulation Analysis with Co-occurrence cues ...
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StarGAN-VC+ASR: StarGAN-based Non-Parallel Voice Conversion Regularized by Automatic Speech Recognition ...
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Unsupervised lexical acquisition of relative spatial concepts using spoken user utterances ...
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Unsupervised lexical acquisition of relative spatial concepts using spoken user utterances ...
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Multiagent Multimodal Categorization for Symbol Emergence: Emergent Communication via Interpersonal Cross-modal Inference ...
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Unsupervised Lexical Acquisition of Relative Spatial Concepts Using Spoken User Utterances ...
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Abstract:
This paper proposes methods for unsupervised lexical acquisition for relative spatial concepts using spoken user utterances. A robot with a flexible spoken dialog system must be able to acquire linguistic representation and its meaning specific to an environment through interactions with humans as children do. Specifically, relative spatial concepts (e.g., front and right) are widely used in our daily lives, however, it is not obvious which object is a reference object when a robot learns relative spatial concepts. Therefore, we propose methods by which a robot without prior knowledge of words can learn relative spatial concepts. The methods are formulated using a probabilistic model to estimate the proper reference objects and distributions representing concepts simultaneously. The experimental results show that relative spatial concepts and a phoneme sequence representing each concept can be learned under the condition that the robot does not know which located object is the reference object. Additionally, ... : 27 pages, 12 figures, submitted to Advanced Robotics ...
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Keyword:
Artificial Intelligence cs.AI; FOS Computer and information sciences; I.2.9; Robotics cs.RO
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URL: https://arxiv.org/abs/2106.08574 https://dx.doi.org/10.48550/arxiv.2106.08574
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Semantic Mapping Based on Spatial Concepts for Grounding Words Related to Places in Daily Environments
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In: Front Robot AI (2019)
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Improved and Scalable Online Learning of Spatial Concepts and Language Models with Mapping ...
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Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping ...
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Spatial Concept Acquisition for a Mobile Robot that Integrates Self-Localization and Unsupervised Word Discovery from Spoken Sentences ...
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