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21
Predicting the dative alternation
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/BresnanEtAL.pdf (2005)
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22
Predicting the dative alternation
In: http://esslli2009.labri.fr/documents/04-BresnanEtAL2007.pdf (2005)
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23
Predicting the dative alternation
In: http://www.stanford.edu/~bresnan/qs-submit.pdf (2005)
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24
Running title:
In: http://www.ualberta.ca/~baayen/publications/PluymaekersEtAlJASA.pdf (2005)
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25
Morphological family size in a morphologically rich language: The case of Finnish compared with Dutch and Hebrew
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/MoscosoBertramSchreuderBaayenJEP2004.pdf (2004)
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26
corresponding author:
In: http://roa.rutgers.edu/files/720-0305/720-BRESNAN-0-0.PDF (2004)
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27
Predicting the unpredictable: Interpreting neutralized segments in Dutch. Language 79.5–38
In: http://muse.jhu.edu/journals/language/v079/79.1ernestus.pdf (2003)
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28
Extracting the lowestfrequency words: Pitfalls and possibilities
In: http://pami.uwaterloo.ca/~nwanas/ftp/Lingusitics/weeber00.pdf (2000)
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29
Extracting the lowest-frequency words: Pitfalls and possibilities
In: http://lhncbc.nlm.nih.gov/lhc/docs/published/2000/pub2000060.pdf (2000)
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30
The Effects of Lexical Specialization on
In: http://acl.ldc.upenn.edu/J/J96/J96-4001.pdf (1996)
Abstract: This paper examines the source of this overestimation bias. It is shown that this bias does not arise due to sentence-bound syntactic constraints, but that it is a direct consequence of topic cohesion in discourse. The nonrandom, clustered appearance of lexically specialized words, often the key words of the text, explains the main trends in the overestimation bias both quantitatively and qualitatively. The effects of nonrandomness are so strong that they introduce an overestimation bias in distributions of units derived from words, such as syllables and digrams. Nonrandom word usage also affects the accuracy of the Good-Turingfrequency estimates which,for the lowest frequencies, reveal a strong underestimation bias. A heuristic adjusted frequency estimate is proposed that, at least for novel-sized texts, is considerably more accurate
URL: http://acl.ldc.upenn.edu/J/J96/J96-4001.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.8769
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31
Derivational productivity and text typology
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/BaayenJQL1994.pdf (1994)
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32
Draft Aviating among the hapax legomena: Morphological grammaticalisation in current British newspaper English
In: http://rdues.bcu.ac.uk/publ/Hapax_Legomena.pdf
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33
Draft Aviating among the hapax legomena: Morphological grammaticalisation in current British newspaper English
In: http://rdues.bcu.ac.uk/publ/Aviating_Among_the_Hapax_Legomena.pdf
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34
Running head: PROCESSING REDUCED WORD FORMS Processing reduced word forms: the sufx restoration effect
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/KempsErnestusSchreuderBaayenBL2004.pdf
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35
How complex simplex words can be. Send proofs to:
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/SchreuderBaayenJML1997.pdf
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36
Themorphological family size effect andmorphology
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/DeJongSchreuderBaayenLCP2000.pdf
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37
Running head: PROSODIC CUES FOR MORPHOLOGICAL COMPLEXITY Prosodic cues for morphological complexity: The case of Dutch plural nouns
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/KempsEtAlMC.pdf
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38
Lexical Dynamics for Low-Frequency Complex Words: A Regression Study Across Tasks and Modalities
In: http://www.sfs.uni-tuebingen.de/%7Ehbaayen/publications/BaayenWurmAycock.pdf
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39
JOURNAL OF MEMORY AND LANGUAGE 37, 118–139 (1997) ARTICLE NO. ML972510 How Complex Simplex Words Can Be
In: https://files.nyu.edu/mp108/public/baayen-jml.pdf
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40
Putting things into context: Exo-lexical effects in sentence reading
In: http://wwwap.wu.ac.at/inst/roman/imm15/workshop3abstracts.pdf
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