ROSMI: A Multimodal Corpus for Map-based Instruction-Giving
ROSMI: A Multimodal Corpus for Map-based Instruction-Giving
复制标题
ROSMI：用于基于地图的教学的多模态语料库
DOI：
10.1145/3382507.3418861
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Helen F. Hastie
中科院分区：
文献类型：
--
作者：
Miltiadis Marios Katsakioris;Ioannis Konstas;P. Mignotte;Helen F. Hastie
我们提出了公开的机器人开放街道地图指令（ROSMI）语料库：通过众包收集的地图和自然语言指令对的丰富的多模态数据集。该语料库的目标是帮助推进最先进的视觉对话任务，包括参考解析和机器人指令理解。这里描述的领域涉及用于检查和应急响应的机器人和自主系统。ROSMI语料库的独特之处在于，它捕获了基于地图的视觉刺激的交互，这些视觉刺激既可供人类阅读，又包含规划和部署机器人和自主系统所需的丰富元数据，从而促进了人机合作。
We present the publicly-available Robot Open Street Map Instructions (ROSMI) corpus: a rich multimodal dataset of map and natural language instruction pairs that was collected via crowdsourcing. The goal of this corpus is to aid in the advancement of state-of-the-art visual-dialogue tasks, including reference resolution and robot-instruction understanding. The domain described here concerns robots and autonomous systems being used for inspection and emergency response. The ROSMI corpus is unique in that it captures interaction grounded in map-based visual stimuli that is both human-readable but also contains rich metadata that is needed to plan and deploy robots and autonomous systems, thus facilitating human-robot teaming.
DOI：
10.18653/v1/d18-1287
发表时间：
2018-09
期刊：
--
影响因子：
--
作者：
Dipendra Misra;Andrew Bennett;Valts Blukis;Eyvind Niklasson;Max Shatkhin;Yoav Artzi
通讯作者：
Dipendra Misra;Andrew Bennett;Valts Blukis;Eyvind Niklasson;Max Shatkhin;Yoav Artzi