Papers with human-robot dialogue
ScoutBot: A Dialogue System for Collaborative Navigation (P18-4)
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Stephanie M. Lukin, Felix Gervits, Cory J. Hayes, Pooja Moolchandani, Anton Leuski, John G. Rogers III, Carlos Sanchez Amaro, Matthew Marge, Clare R. Voss, David Traum
| Challenge: | Demo will allow users to issue unconstrained spoken language commands to ScoutBot. |
| Approach: | The demonstration will allow users to issue unconstrained spoken language commands to ScoutBot. |
| Outcome: | The demonstration will allow users to issue unconstrained spoken language commands to ScoutBot. |
Dialogue-AMR: Abstract Meaning Representation for Dialogue (2020.lrec-1)
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Claire Bonial, Lucia Donatelli, Mitchell Abrams, Stephanie M. Lukin, Stephen Tratz, Matthew Marge, Ron Artstein, David Traum, Clare Voss
| Challenge: | Abstract Meaning Representation (AMR) does not capture the illocutionary force or speaker’s intended contribution in the broader dialogue context. |
| Approach: | They propose a schema that enriches Abstract Meaning Representation (AMR) it provides a semantic representation for facilitating Natural Language Understanding (NLU) in dialogue systems. |
| Outcome: | The proposed schema provides a semantic representation for facilitating Natural Language Understanding (NLU) in human-robot dialogue systems. |
A Two-Level Interpretation of Modality in Human-Robot Dialogue (2020.coling-main)
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| Challenge: | modal expressions are used to communicate and align world knowledge, but there is no obvious manner to ground them in the shared environment. |
| Approach: | They propose a two-level annotation scheme for modality that captures both content and intent and a task-oriented, pragmatic representation that maps to our robot's capabilities. |
| Outcome: | The proposed model can be grounded and dynamically interpreted. |
SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus (2024.lrec-main)
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Stephanie M. Lukin, Claire Bonial, Matthew Marge, Taylor A. Hudson, Cory J. Hayes, Kimberly Pollard, Anthony Baker, Ashley N. Foots, Ron Artstein, Felix Gervits, Mitchell Abrams, Cassidy Henry, Lucia Donatelli, Anton Leuski, Susan G. Hill, David Traum, Clare Voss
| Challenge: | The corpus contains 89,056 utterances and 310,095 words from 278 dialogues averaging 320 utterrances per dialogue. |
| Approach: | They present the Situated Corpus Of Understanding Transactions, a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. |
| Outcome: | The Situated Corpus Of Understanding Transactions (SCOUT) contains 89,056 utterances and 310,095 words from 278 dialogues averaging 320 utterrances per dialogue. |