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        <title>Noisy-context surprisal as a human sentence processing cost model</title>
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            <namePart type="given">Mirella</namePart>
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    <abstract>We use the noisy-channel theory of human sentence comprehension to develop an incremental processing cost model that unifies and extends key features of expectation-based and memory-based models. In this model, which we call noisy-context surprisal, the processing cost of a word is the surprisal of the word given a noisy representation of the preceding context. We show that this model accounts for an outstanding puzzle in sentence comprehension, language-dependent structural forgetting effects (Gibson and Thomas, 1999; Vasishth et al., 2010; Frank et al., 2016), which are previously not well modeled by either expectation-based or memory-based approaches. Additionally, we show that this model derives and generalizes locality effects (Gibson, 1998; Demberg and Keller, 2008), a signature prediction of memory-based models. We give corpus-based evidence for a key assumption in this derivation.</abstract>
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%0 Conference Proceedings
%T Noisy-context surprisal as a human sentence processing cost model
%A Futrell, Richard
%A Levy, Roger
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F futrell-levy-2017-noisy
%X We use the noisy-channel theory of human sentence comprehension to develop an incremental processing cost model that unifies and extends key features of expectation-based and memory-based models. In this model, which we call noisy-context surprisal, the processing cost of a word is the surprisal of the word given a noisy representation of the preceding context. We show that this model accounts for an outstanding puzzle in sentence comprehension, language-dependent structural forgetting effects (Gibson and Thomas, 1999; Vasishth et al., 2010; Frank et al., 2016), which are previously not well modeled by either expectation-based or memory-based approaches. Additionally, we show that this model derives and generalizes locality effects (Gibson, 1998; Demberg and Keller, 2008), a signature prediction of memory-based models. We give corpus-based evidence for a key assumption in this derivation.
%U https://aclanthology.org/E17-1065
%P 688-698

Markdown (Informal)

[Noisy-context surprisal as a human sentence processing cost model](https://aclanthology.org/E17-1065) (Futrell & Levy, EACL 2017)

• Noisy-context surprisal as a human sentence processing cost model (Futrell & Levy, EACL 2017)

ACL

• Richard Futrell and Roger Levy. 2017. Noisy-context surprisal as a human sentence processing cost model. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 688–698, Valencia, Spain. Association for Computational Linguistics.