Papers by Ron Artstein

6 papers
Dialogue-AMR: Abstract Meaning Representation for Dialogue (2020.lrec-1)

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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.
The Niki and Julie Corpus: Collaborative Multimodal Dialogues between Humans, Robots, and Virtual Agents (L18-1)

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Challenge: Niki and Julie corpus contains more than 600 dialogues between humans and robots . corpus includes audio and video recordings, results of ranking tasks, questionnaire responses .
Approach: the corpus contains more than 600 dialogues between human participants and a robot . the dialogues are part of a collaborative item-ranking task designed to measure influence .
Outcome: the corpus contains more than 600 dialogues between human participants and a robot or virtual agent . the dialogues contain conversational errors by the robot, which simulates typical of modern automated agents .
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.
Edit me: A Corpus and a Framework for Understanding Natural Language Image Editing (L18-1)

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Challenge: a corpus of image edit requests is elicited for real world images, and an annotation framework is developed . evaluators evaluate crowd-sourced annotation as a means of efficiently creating a sizable corpus at a reasonable cost.
Approach: They propose a natural language interface for interacting with an image editing program . they propose an annotation framework for understanding natural language requests .
Outcome: The proposed tool interprets image edit requests and maps them to actionable commands.
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.
Chahta Anumpa: A multimodal corpus of the Choctaw Language (L18-1)

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Challenge: a corpus of texts representing the Choctaw language is presented for use in linguistic studies.
Approach: They present a general use corpus for the Choctaw language in the southeastern u.s. the corpus contains audio, video, and text resources, with many texts also translated in english.
Outcome: The proposed corpus provides documentation support for the threatened language . the data set includes audio, video, and text resources .

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