@inproceedings{5226726253fa48438b93456af686ed97,
title = "Natural language grounding and grammar induction for robotic manipulation commands",
abstract = "We present a cognitively plausible system capable of acquiring knowledge in language and vision from pairs of short video clips and linguistic descriptions. The aim of this work is to teach a robot manipulator how to execute natural language commands by demonstration. This is achieved by first learning a set of visual 'concepts' that abstract the visual feature spaces into concepts that have human-level meaning. Second, learning the mapping/grounding between words and the extracted visual concepts. Third, inducing grammar rules via a semantic representation known as Robot Control Language (RCL). We evaluate our approach against state-of-the-art supervised and unsupervised grounding and grammar induction systems, and show that a robot can learn to execute never seenbefore commands from pairs of unlabelled linguistic and visual inputs.",
author = "M. Alomari and P. Duckworth and M. Hawasly and Hogg, {D. C.} and Cohn, {A. G.}",
note = "Publisher Copyright: {\textcopyright} 2017 Proceedings of the 1st Workshop on Language Grounding for Robotics, RoboNLP 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017. All rights reserved.; 1st Workshop on Language Grounding for Robotics, RoboNLP 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 ; Conference date: 03-08-2017",
year = "2017",
language = "English",
series = "Proceedings of the 1st Workshop on Language Grounding for Robotics, RoboNLP 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017",
publisher = "Association for Computational Linguistics (ACL)",
pages = "35--43",
editor = "Mohit Bansal and Cynthia Matuszek and Jacob Andreas and Yoav Artzi and Yonatan Bisk",
booktitle = "Proceedings of the 1st Workshop on Language Grounding for Robotics, RoboNLP 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017",
address = "United States",
}