Papers by Felix Gervits

5 papers
ScoutBot: A Dialogue System for Collaborative Navigation (P18-4)

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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 Structure Annotation for Multi-Floor Interaction (L18-1)

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Challenge: Existing annotation schemes do not address dialogue structure.
Approach: They propose an annotation scheme for meso-level dialogue structure that clusters utterances from multiple participants and floors into units according to realization of an initiator's intent.
Outcome: The proposed annotation scheme is used to annotate a corpus of human-robot interaction dialogues.
Towards a Conversation-Analytic Taxonomy of Speech Overlap (L18-1)

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Challenge: a taxonomy for classifying speech overlap in natural language dialogue is presented . the scheme classifies overlap on the basis of several features, including onset point, local dialogue history, and management behavior.
Approach: They propose a taxonomy for classifying speech overlap in natural language dialogue . they describe the various dimensions of the scheme and show how it was applied to a corpus of collaborative dialogue based on onset point, dialogue history, and management behavior .
Outcome: The proposed taxonomy classifies overlap on the basis of onset point, dialogue history, management behavior.
DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents (2022.findings-emnlp)

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Challenge: Empowering autonomous driving agents with the ability to navigate in a continuous and dynamic environment is critical.
Approach: They propose 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.
Outcome: The proposed platform enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.
SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus (2024.lrec-main)

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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.

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