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Found 18 papers, 6 papers with code
A System For Robot Concept Learning Through Situated Dialogue
We evaluate the system by comparing learning efficiency to a human baseline in a collaborative reference resolution task and show that the system is effective and efficient in learning new concepts, and that it can informatively generate explanations about its behavior.
Human-Robot Dialogue Annotation for Multi-Modal Common Ground
In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems participating in collaborative, natural language dialogue, and to enable common ground with human partners.
SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus
We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration.
Dialogue with Robots: Proposals for Broadening Participation and Research in the SLIVAR Community
The ability to interact with machines using natural human language is becoming not just commonplace, but expected.
DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents
To this end, we introduce Dialogue On the ROad To Handle Irregular Events (DOROTHIE), a novel interactive simulation platform that enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.
Decision-Theoretic Question Generation for Situated Reference Resolution: An Empirical Study and Computational Model
Dialogue agents that interact with humans in situated environments need to manage referential ambiguity across multiple modalities and ask for help as needed.
How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue Corpus
Intelligent agents that are confronted with novel concepts in situated environments will need to ask their human teammates questions to learn about the physical world.
Spoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop
Fourth, more powerful adaptation methods are needed, to enable robots to communicate in new environments, for new tasks, and with diverse user populations, without extensive re-engineering or the collection of massive training data.
Dialogue-AMR: Abstract Meaning Representation for Dialogue
This paper describes a schema that enriches Abstract Meaning Representation (AMR) in order to provide a semantic representation for facilitating Natural Language Understanding (NLU) in dialogue systems.
Abstract Meaning Representation
Natural Language Understanding
A Research Platform for Multi-Robot Dialogue with Humans
This paper presents a research platform that supports spoken dialogue interaction with multiple robots.
B. Rex: a dialogue agent for book recommendations
We present B. Rex, a dialogue agent for book recommendations.
ScoutBot: A Dialogue System for Collaborative Navigation
ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments.
Consequences and Factors of Stylistic Differences in Human-Robot Dialogue
This paper identifies stylistic differences in instruction-giving observed in a corpus of human-robot dialogue.
Laying Down the Yellow Brick Road: Development of a Wizard-of-Oz Interface for Collecting Human-Robot Dialogue
We describe the adaptation and refinement of a graphical user interface designed to facilitate a Wizard-of-Oz (WoZ) approach to collecting human-robot dialogue data.
Exploring Variation of Natural Human Commands to a Robot in a Collaborative Navigation Task
Robot-directed communication is variable, and may change based on human perception of robot capabilities.
Applying the Wizard-of-Oz Technique to Multimodal Human-Robot Dialogue
Our overall program objective is to provide more natural ways for soldiers to interact and communicate with robots, much like how soldiers communicate with other soldiers today.
