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1
Parallel processing in speech perception with local and global representations of linguistic context
In: eLife (2022)
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2
Using surprisal and fMRI to map the neural bases of broad and local contextual prediction during natural language comprehension ...
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3
Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task
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4
Connecting Documents, Words, and Languages Using Topic Models
Yang, Weiwei. - 2019
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5
Assessing Composition in Sentence Vector Representations ...
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6
Relating lexical and syntactic processes in language: Bridging research in humans and machines
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7
Guided Probabilistic Topic Models for Agenda-setting and Framing
Nguyen, Viet An. - 2015
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8
Soft syntactic constraints for Arabic-English hierarchical phrase-based translation
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 26 (2012) 1-2, 137-157
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OLC Linguistik
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9
Crowdsourced Monolingual Translation
Hu, Chang. - 2012
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10
Decision Tree-based Syntactic Language Modeling
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11
Modeling Dependencies in Natural Languages with Latent Variables
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12
Exploiting syntactic relationships in a phrase-based decoder: an exploration
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 24 (2010) 2, 123-140
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OLC Linguistik
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13
Gibbs Sampling for the Uninitiated
In: DTIC (2010)
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14
Structured local exponential models for machine translation
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15
A Formal Model of Ambiguity and its Applications in Machine Translation
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16
Extending Phrase-Based Decoding with a Dependency-Based Reordering Model
In: DTIC (2009)
Abstract: Phrase-based decoding is conceptually simple and straightforward to implement, at the cost of drastically oversimplified reordering models. Syntactically aware models make it possible to capture linguistically relevant relationships in order to improve word order, but they can be more complex to implement and optimize. In this paper, we explore a new middle ground between phrase-based and syntactically informed statistical MT, in the form of a model that supplements conventional, non-hierarchical phrase-based techniques with linguistically informed reordering based on syntactic dependency trees. The key idea is to exploit linguistically-informed hierarchical structures only for those dependencies that cannot be captured within a single flat phrase. For very local dependencies we leverage the success of conventional phrase-based approaches, which provide a sequence of target-language words appropriately ordered and ready-made with the appropriate agreement morphology. Working with dependency trees rather than constituency trees allows us to take advantage of the flexibility of phrase-based systems to treat non-constituent fragments as phrases. We do impose a requirement - that the fragment be a novel sort of "dependency constituent" - on what can be translated as a phrase, but this is much weaker than the requirement that phrases be traditional linguistic constituents, which has often proven too restrictive in MT systems. ; UMIACS-TR-2009-15. Sponosred in part by the Defense Advanced Research Projects Agency.
Keyword: *MACHINE TRANSLATION; Cybernetics; CZECH LANGUAGE; CZECH-ENGLISH TRANSLATION EXPERIMENTS; DECODING; ENGLISH LANGUAGE; EXPERIMENTAL DESIGN; Linguistics; PHRASE BASED DECODING; PHRASE STRUCTURE GRAMMARS; REORDERING MODELS; STATISTICAL MACHINE TRANSLATION; SYNTACTIC DEPENDENCY TREES; SYNTAX; TOPOLOGY
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA522961
http://www.dtic.mil/docs/citations/ADA522961
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17
Extending Phrase-Based Decoding with a Dependency-Based Reordering Model
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18
COMPUTATIONAL ANALYSIS OF THE CONVERSATIONAL DYNAMICS OF THE UNITED STATES SUPREME COURT
Hawes, Timothy. - 2009
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19
Fine-Grained Linguistic Soft Constraints on Statistical Natural Language Processing Models
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20
Generalizing Word Lattice Translation
In: DTIC (2008)
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