@inproceedings{kery-etal-2019-es,
    title = "?`{E}s un pl{\'a}tano? Exploring the Application of a Physically Grounded Language Acquisition System to {S}panish",
    author = "Kery, Caroline  and
      Ferraro, Francis  and
      Matuszek, Cynthia",
    editor = "Bhatia, Archna  and
      Bisk, Yonatan  and
      Kordjamshidi, Parisa  and
      Thomason, Jesse",
    booktitle = "Proceedings of the Combined Workshop on Spatial Language Understanding ({S}p{LU}) and Grounded Communication for Robotics ({R}obo{NLP})",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-1602",
    doi = "10.18653/v1/W19-1602",
    pages = "7--17",
    abstract = "In this paper we describe a multilingual grounded language learning system adapted from an English-only system. This system learns the meaning of words used in crowd-sourced descriptions by grounding them in the physical representations of the objects they are describing. Our work presents a framework to compare the performance of the system when applied to a new language and to identify modifications necessary to attain equal performance, with the goal of enhancing the ability of robots to learn language from a more diverse range of people. We then demonstrate this system with Spanish, through first analyzing the performance of translated Spanish, and then extending this analysis to a new corpus of crowd-sourced Spanish language data. We find that with small modifications, the system is able to learn color, object, and shape words with comparable performance between languages.",
}