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dc.contributor.author
Pimentel, Tiago
dc.contributor.author
Cotterell, Ryan
dc.contributor.author
Roark, Brian
dc.contributor.editor
Merlo, Paola
dc.contributor.editor
Tiedemann, Jörg
dc.contributor.editor
Tsarfaty, Reut
dc.date.accessioned
2021-12-07T08:24:49Z
dc.date.available
2021-12-06T19:46:58Z
dc.date.available
2021-12-07T08:24:49Z
dc.date.issued
2021-04
dc.identifier.isbn
978-1-954085-02-2
en_US
dc.identifier.other
10.18653/v1/2021.eacl-main.3
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/518997
dc.identifier.doi
10.3929/ethz-b-000518997
dc.description.abstract
Psycholinguistic studies of human word processing and lexical access provide ample evidence of the preferred nature of word-initial versus word-final segments, e.g., in terms of attention paid by listeners (greater) or the likelihood of reduction by speakers (lower). This has led to the conjecture—as in Wedel et al. (2019b), but common elsewhere—that languages have evolved to provide more information earlier in words than later. Information-theoretic methods to establish such tendencies in lexicons have suffered from several methodological shortcomings that leave open the question of whether this high word-initial informativeness is actually a property of the lexicon or simply an artefact of the incremental nature of recognition. In this paper, we point out the confounds in existing methods for comparing the informativeness of segments early in the word versus later in the word, and present several new measures that avoid these confounds. When controlling for these confounds, we still find evidence across hundreds of languages that indeed there is a cross-linguistic tendency to front-load information in words.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Association for Computational Linguistics
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Disambiguatory Signals are Stronger in Word-initial Positions
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.book.title
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
en_US
ethz.pages.start
31
en_US
ethz.pages.end
41
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.event
16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)
en_US
ethz.event.location
Online
en_US
ethz.event.date
April 19-23, 2021
en_US
ethz.publication.place
Stroudsburg, PA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::09682 - Cotterell, Ryan / Cotterell, Ryan
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::09682 - Cotterell, Ryan / Cotterell, Ryan
en_US
ethz.date.deposited
2021-12-06T19:47:04Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-12-07T08:25:06Z
ethz.rosetta.lastUpdated
2023-02-06T23:24:54Z
ethz.rosetta.versionExported
true
ethz.COinS
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