Search Results for author: Brian McMahan

Found 6 papers, 1 papers with code

Analyzing Speaker Strategy in Referential Communication

no code implementations SIGDIAL (ACL) 2020 Brian McMahan, Matthew Stone

We analyze a corpus of referential communication through the lens of quantitative models of speaker reasoning.

Discourse Coherence, Reference Grounding and Goal Oriented Dialogue

no code implementations8 Jul 2020 Baber Khalid, Malihe Alikhani, Michael Fellner, Brian McMahan, Matthew Stone

Prior approaches to realizing mixed-initiative human--computer referential communication have adopted information-state or collaborative problem-solving approaches.

Listening to the World Improves Speech Command Recognition

no code implementations23 Oct 2017 Brian McMahan, Delip Rao

Our key finding is that not only is it possible to transfer representations from an unrelated task like environmental sound classification to a voice-focused task like speech command recognition, but also that doing so improves accuracies significantly.

Environmental Sound Classification General Classification +1

Syntactic realization with data-driven neural tree grammars

1 code implementation COLING 2016 Brian McMahan, Matthew Stone

A key component in surface realization in natural language generation is to choose concrete syntactic relationships to express a target meaning.

Language Modelling Text Generation

A Bayesian Model of Grounded Color Semantics

no code implementations TACL 2015 Brian McMahan, Matthew Stone

Natural language meanings allow speakers to encode important real-world distinctions, but corpora of grounded language use also reveal that speakers categorize the world in different ways and describe situations with different terminology.

Language understanding

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