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Document and corpus level inference for unsupervised and transductive learning of information structure of scientic documents
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In: http://aclweb.org/anthology/C/C12/C12-2097.pdf (2012)
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| 2 |
Home
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In: http://wings.buffalo.edu/linguistics//people/faculty/vanvalin/rrg/RRGBib_2012_5_12.pdf (2012)
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General
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In: http://uu.diva-portal.org/smash/get/diva2%3A275878/FULLTEXT03.pdf (2009)
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| 4 |
Contents
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In: http://www.tex.ac.uk/tex-archive/biblio/bibtex/contrib/babelbib/doc/latex/babelbib/babelbib.pdf (2009)
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| 5 |
1 Role and Reference Grammar*
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In: http://linguistics.buffalo.edu/people/faculty/vanvalin/rrg/RRGBib_Oct08.pdf (2008)
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| 6 |
Affixal salience and the processing of derivational morphology: The role of suffix allomorphy
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In: http://users.utu.fi/rayber/articles/JBNLCP_006986.pdf (2006)
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| 7 |
Morfessor and hutmegs: Unsupervised morpheme segmentation for highlyinflecting and compounding languages
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In: http://www.cis.hut.fi/krista/papers/Creutz05hlt.pdf (2005)
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| 8 |
Morfessor and hutmegs: Unsupervised morpheme segmentation for highlyinflecting and compounding languages
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In: http://www.cis.hut.fi/krista/papers/Creutz05hlt.ps (2005)
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| 9 |
Empirical tests of the Gradual Learning Algorithm. Linguistic Inquiry 32
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In: http://www.linguistics.ucla.edu/people/hayes/Papers/BoersmaAndHayes2001GLA.pdf (2001)
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| 10 |
Empirical tests of the gradual learning algorithm. Linguistic Inquiry 32(1):45–86
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In: http://www.phil-fak.uni-duesseldorf.de/summerschool2002/Aissen5.pdf (2001)
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| 11 |
Empirical tests of the gradual learning algorithm. Linguistic Inquiry 32.45–86
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In: http://www.fon.hum.uva.nl/paul/papers/BoersmaHayes_li2001.pdf (2001)
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| 12 |
Empirical tests of the Gradual Learning Algorithm
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In: http://www.humnet.ucla.edu/humnet/linguistics/people/hayes/GLA/gla.pdf (2001)
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Abstract:
The Gradual Learning Algorithm (Boersma 1997) is a constraint ranking algorithm for learning Optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smolensky (1993, 1996, 1998, 2000), which initiated the learnability research program for Optimality Theory. We argue that the Gradual Learning Algorithm has a number of special advantages: it can learn free variation, deal effectively with noisy learning data, and account for gradient wellformedness judgments. The case studies we examine involve Ilokano reduplication and metathesis, Finnish genitive plurals, and the distribution of English light and dark /l/.
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Keyword:
Finnish; Ilokano; Learnability; Optimality Theory; variation
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.2795
http://www.humnet.ucla.edu/humnet/linguistics/people/hayes/GLA/gla.pdf
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| 13 |
The speechdat-car multilingual speech databases for in-car applciations
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In: http://perso.telecom-paristech.fr/~grichard/Publications/eurospeech99.pdf (1999)
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The Speechdat-Car Multilingual Speech Databases For In-Car Applications: Some First Validation Results
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In: http://iris1.let.kun.nl/literature/heuvel.1999.4.ps (1999)
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| 15 |
Morphemes as Necessary Concept for Structures Discovery from Untagged Corpora
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In: http://users.info.unicaen.fr/~dejean/divers/./travail/articles/pgll.ps (1998)
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| 16 |
Morphemes as Necessary Concept for Structures Discovery from Untagged Corpora
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In: http://lcg-www.uia.ac.be/conll98/ps/295298de.ps (1998)
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| 17 |
Morphemes as Necessary Concept for Structures Discovery from Untagged Corpora
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In: http://acl.ldc.upenn.edu/W/W98/W98-1239.pdf (1998)
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| 18 |
Handling Compound Nouns in a Swedish Speech-Understanding System
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In: http://kidwelly.cam.sri.com/tr/crc062/paper.ps.Z (1996)
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| 19 |
Handling Compound Nouns in a Swedish Speech-Understanding System
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In: ftp://ftp.speech.sri.com/pub/papers/icslp96-compounds.ps.gz (1996)
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| 20 |
Handling Compound Nouns in a Swedish Speech-Understanding System
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In: http://www.asel.udel.edu/icslp/cdrom/vol1/594/a594.pdf (1996)
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