M
Matthew Marge
Researcher at United States Army Research Laboratory
Publications - 47
Citations - 1089
Matthew Marge is an academic researcher from United States Army Research Laboratory. The author has contributed to research in topics: Robot & Human–robot interaction. The author has an hindex of 14, co-authored 45 publications receiving 920 citations. Previous affiliations of Matthew Marge include United States Naval Research Laboratory & Stony Brook University.
Papers
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Proceedings ArticleDOI
Using the Amazon Mechanical Turk for transcription of spoken language
TL;DR: It was found that transcriptions from MTurk workers were generally quite accurate, and when transcripts for the same utterance produced by multiple workers were combined using the ROVER voting scheme, the accuracy of the combined transcript rivaled that observed for conventional transcription methods.
Book ChapterDOI
Evaluating evaluation methods for generation in the presence of variation
TL;DR: This paper compares the performance of several automatic evaluation metrics using a corpus of automatically generated paraphrases and shows that these evaluation metrics can at least partially measure adequacy, but are not good measures of fluency.
Proceedings ArticleDOI
Effects of adaptive robot dialogue on information exchange and social relations
TL;DR: This work suggests adaptation in human-robot interaction has consequences for both task performance and social cohesion, and suggests that people may be more sensitive to social relations with robots when under task or time pressure.
Proceedings Article
Spatial representation and reasoning for human-robot collaboration
William G. Kennedy,Magdalena D. Bugajska,Matthew Marge,William Adams,Benjamin R. Fransen,Dennis Perzanowski,Alan C. Schultz,J. Gregory Trafton +7 more
TL;DR: The cognitive modeling system, ACT-R, is used with an added spatial module to support the robot's spatial reasoning and its integration of metric, symbolic, and cognitive layers of spatial representation and reasoning for its individual and team behavior.
Proceedings Article
Dialogue-AMR: Abstract Meaning Representation for Dialogue.
Claire Bonial,Lucia Donatelli,Mitchell Abrams,Stephanie M. Lukin,Stephen Tratz,Matthew Marge,Ron Artstein,David Traum,Clare R. Voss +8 more
TL;DR: A schema that enriches Abstract Meaning Representation (AMR) in order to provide a semantic representation for facilitating Natural Language Understanding (NLU) in dialogue systems is described and an enhanced AMR that represents not only the content of an utterance, but the illocutionary force behind it, as well as tense and aspect is presented.