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        <title>A large-scale study of the effects of word frequency and predictability in naturalistic reading</title>
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        <namePart type="given">Cory</namePart>
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            <title>Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)</title>
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        <name type="personal">
            <namePart type="given">Jill</namePart>
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        <name type="personal">
            <namePart type="given">Christy</namePart>
            <namePart type="family">Doran</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
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    <abstract>A number of psycholinguistic studies have factorially manipulated words’ contextual predictabilities and corpus frequencies and shown separable effects of each on measures of human sentence processing, a pattern which has been used to support distinct mechanisms underlying prediction on the one hand and lexical retrieval on the other. This paper examines the generalizability of this finding to more realistic conditions of sentence processing by studying effects of frequency and predictability in three large-scale naturalistic reading corpora. Results show significant effects of word frequency and predictability in isolation but no effect of frequency over and above predictability, and thus do not provide evidence of distinct mechanisms. The non-replication of separable effects in a naturalistic setting raises doubts about the existence of such a distinction in everyday sentence comprehension. Instead, these results are consistent with previous claims that apparent effects of frequency are underlyingly effects of predictability.</abstract>
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    <identifier type="doi">10.18653/v1/N19-1413</identifier>
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%0 Conference Proceedings
%T A large-scale study of the effects of word frequency and predictability in naturalistic reading
%A Shain, Cory
%Y Burstein, Jill
%Y Doran, Christy
%Y Solorio, Thamar
%S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F shain-2019-large
%X A number of psycholinguistic studies have factorially manipulated words’ contextual predictabilities and corpus frequencies and shown separable effects of each on measures of human sentence processing, a pattern which has been used to support distinct mechanisms underlying prediction on the one hand and lexical retrieval on the other. This paper examines the generalizability of this finding to more realistic conditions of sentence processing by studying effects of frequency and predictability in three large-scale naturalistic reading corpora. Results show significant effects of word frequency and predictability in isolation but no effect of frequency over and above predictability, and thus do not provide evidence of distinct mechanisms. The non-replication of separable effects in a naturalistic setting raises doubts about the existence of such a distinction in everyday sentence comprehension. Instead, these results are consistent with previous claims that apparent effects of frequency are underlyingly effects of predictability.
%R 10.18653/v1/N19-1413
%U https://aclanthology.org/N19-1413
%U https://doi.org/10.18653/v1/N19-1413
%P 4086-4094

Markdown (Informal)

[A large-scale study of the effects of word frequency and predictability in naturalistic reading](https://aclanthology.org/N19-1413) (Shain, NAACL 2019)

• A large-scale study of the effects of word frequency and predictability in naturalistic reading (Shain, NAACL 2019)

ACL

• Cory Shain. 2019. A large-scale study of the effects of word frequency and predictability in naturalistic reading. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 4086–4094, Minneapolis, Minnesota. Association for Computational Linguistics.