The challenge of language grounding is to fully understand natural language by grounding language in real-world referents. While AI techniques are available, the widespread adoption and effectiveness of such technologies for human-robot teams relies critically on user trust. This survey provides three contributions relating to the newly emerging field of trust in language grounding, including a) an overview of language grounding research in terms of AI technologies, data sets, and user interfaces; b) six hypothesised trust factors relevant to language grounding, which are tested empirically on a human-robot cleaning team; and c) future research directions for trust in language grounding.
翻译:语言定位的挑战是通过在现实世界的参考文献中使用语言来充分理解自然语言。虽然有人工智能技术,但人类机器人团队广泛采用这类技术及其有效性的关键取决于用户信任度。这一调查提供了与新兴的语言定位信任领域有关的三项贡献,包括:(a) 从人工智能技术、数据集和用户界面的角度概述语言定位研究;(b) 与语言定位有关的六个假设信任因素,这些假设信任因素在人类机器人清洁小组中进行了经验测试;(c) 未来语言定位信任研究方向。