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Dive into the research topics where Timothy J. O'Donnell is active.

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Featured researches published by Timothy J. O'Donnell.


Proceedings of the National Academy of Sciences of the United States of America | 2013

Grammatical morphology as a source of early number word meanings

Alhanouf Almoammer; Jessica Sullivan; Chris Donlan; Franc Marušič; Rok Zaucer; Timothy J. O'Donnell; David Barner

Significance Languages vary in how they grammatically mark number (e.g., in nouns, verbs, and so forth). We test the effects of this variability on learning number words—for example, one, two, three—by investigating children learning Slovenian and Saudi Arabic, which have singular-plural marking, but also dual marking (for sets of two). We find that learning the dual is associated with faster learning of the meaning of two than in any previously studied language, even when accompanied by less experience with counting. We conclude that although exposure to counting is important to learning number word meanings, hearing number words used outside of these routines—in the quantificational structures of language—may also be highly important in early acquisition. How does cross-linguistic variation in linguistic structure affect children’s acquisition of early number word meanings? We tested this question by investigating number word learning in two unrelated languages that feature a tripartite singular-dual-plural distinction: Slovenian and Saudi Arabic. We found that learning dual morphology affects children’s acquisition of the number word two in both languages, relative to English. Children who knew the meaning of two were surprisingly frequent in the dual languages, relative to English. Furthermore, Slovenian children were faster to learn two than children learning English, despite being less-competent counters. Finally, in both Slovenian and Saudi Arabic, comprehension of the dual was correlated with knowledge of two and higher number words.


Language, cognition and neuroscience | 2015

The Causes and Consequences Explicit in Verbs

Joshua K. Hartshorne; Timothy J. O'Donnell; Joshua B. Tenenbaum

Interpretation of a pronoun in one clause can be systematically affected by the verb in the previous clause. Compare Archibald angered Bartholomew because he … (he = Archibald) with Archibald criticised Bartholomew because he … (he = Bartholomew). While it is clear that meaning plays a critical role, it is unclear whether that meaning is directly encoded in the verb or, alternatively, inferred from world knowledge. We report evidence favouring the former account. We elicited pronoun biases for 502 verbs from seven Levin verb classes in two discourse contexts (implicit causality and implicit consequentiality), showing that in both contexts, verb class reliably predicts pronoun bias. These results confirm and extend recent findings about implicit causality and represent the first such study for implicit consequentiality. We discuss these findings in the context of recent work in semantics, and also develop a new, probabilistic generative account of pronoun interpretation.


empirical methods in natural language processing | 2015

A model of rapid phonotactic generalization

Tal Linzen; Timothy J. O'Donnell

The phonotactics of a language describes the ways in which the sounds of the language combine to form possible morphemes and words. Humans can learn phonotactic patterns at the level of abstract classes, generalizing across sounds (e.g., “words can end in a voiced stop”). Moreover, they rapidly acquire these generalizations, even before they acquire soundspecific patterns. We present a probabilistic model intended to capture this early


Proceedings of the Sixth Workshop on Cognitive Aspects of Computational Language Learning | 2015

Evaluating Models of Computation and Storage in Human Sentence Processing

Thang Luong; Timothy J. O'Donnell; Noah D. Goodman

We examine the ability of several models of computation and storage to explain reading time data. Specifically, wedemonstrate on both the Dundee and the MIT reading time corpora, that fragment grammars, a model that optimizes the tradeoff between computation and storage, is able to better explain people’s reaction times than two baseline models which exclusively favor either storage or computation. Additionally, we make a contribution by extending an existing incremental parser to handle more general grammars and scale well to larger rule and data sets. 1


Trends in Cognitive Sciences | 2005

Using mathematical models of language experimentally.

Timothy J. O'Donnell; Marc D. Hauser; W. Tecumseh Fitch


Cognitive Science | 2011

Productivity and reuse in language

Jesse Snedeker; Timothy J. O'Donnell


Transactions of the Association for Computational Linguistics | 2015

Unsupervised Lexicon Discovery from Acoustic Input

Chia-ying Lee; Timothy J. O'Donnell; James R. Glass


Archive | 2009

Fragment Grammars: Exploring Computation and Reuse in Language

Timothy J. O'Donnell; Noah D. Goodman; Joshua B. Tenenbaum


Archive | 2015

Productivity and Reuse in Language: A Theory of Linguistic Computation and Storage

Timothy J. O'Donnell


Proceedings of the Fourth Annual Workshop on Cognitive Modeling and Computational Linguistics (CMCL) | 2013

Learning non-concatenative morphology

Michelle Alison Fullwood; Timothy J. O'Donnell

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Joshua B. Tenenbaum

Massachusetts Institute of Technology

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Joshua K. Hartshorne

Massachusetts Institute of Technology

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Leon Bergen

Massachusetts Institute of Technology

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Edward Gibson

Massachusetts Institute of Technology

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Adam Albright

Massachusetts Institute of Technology

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Chia-ying Lee

Massachusetts Institute of Technology

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David Barner

University of California

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