no code implementations • 3 Feb 2016 • Akira Taniguchi, Tadahiro Taniguchi, Tetsunari Inamura
In this paper, we propose a novel unsupervised learning method for the lexical acquisition of words related to places visited by robots, from human continuous speech signals.
5 code implementations • 15 Apr 2017 • Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi, Tetsunari Inamura
We have proposed a nonparametric Bayesian spatial concept acquisition model (SpCoA).
3 code implementations • 9 Mar 2018 • Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi, Tetsunari Inamura
We propose a novel online learning algorithm, called SpCoSLAM 2. 0, for spatial concepts and lexical acquisition with high accuracy and scalability.
no code implementations • 6 Mar 2019 • Miguel Vasco, Francisco S. Melo, David Martins de Matos, Ana Paiva, Tetsunari Inamura
In this work we present \textit{motion concepts}, a novel multimodal representation of human actions in a household environment.
1 code implementation • 18 Feb 2020 • Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi, Tetsunari Inamura
The aim of this study is to enable a mobile robot to perform navigational tasks with human speech instructions, such as `Go to the kitchen', via probabilistic inference on a Bayesian generative model using spatial concepts.