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Volumn , Issue , 2016, Pages 634-643

Morphological inflection generation using character sequence to sequence learning

Author keywords

[No Author keywords available]

Indexed keywords

ENCODER-DECODER; LANGUAGE INDEPENDENTS; SEMI-SUPERVISED; SEQUENCE LEARNING; STATE OF THE ART;

EID: 84994149005     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/n16-1077     Document Type: Conference Paper
Times cited : (113)

References (53)
  • 1
    • 84905690484 scopus 로고    scopus 로고
    • Semi-supervised learning of morphological paradigms and lexicons
    • Malin Ahlberg, Markus Forsberg, and Mans Hulden. 2014. Semi-supervised learning of morphological paradigms and lexicons. In Proc. of EACL.
    • (2014) Proc. of EACL
    • Ahlberg, M.1    Forsberg, M.2    Hulden, M.3
  • 2
    • 84949839549 scopus 로고    scopus 로고
    • Paradigm classification in supervised learning of morphology
    • Malin Ahlberg, Markus Forsberg, and Mans Hulden. 2015. Paradigm classification in supervised learning of morphology. Proc. of NAACL.
    • (2015) Proc. of NAACL
    • Ahlberg, M.1    Forsberg, M.2    Hulden, M.3
  • 4
    • 85083953689 scopus 로고    scopus 로고
    • Neural machine translation by jointly learning to align and translate
    • Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In Proc. of ICLR.
    • (2015) Proc. of ICLR
    • Bahdanau, D.1    Cho, K.2    Bengio, Y.3
  • 5
    • 84959879897 scopus 로고    scopus 로고
    • Improved transition-based parsing by modeling characters instead of words with lstms
    • Miguel Ballesteros, Chris Dyer, and Noah A. Smith. 2015. Improved transition-based parsing by modeling characters instead of words with lstms. In Proc. of EMNLP.
    • (2015) Proc. of EMNLP
    • Ballesteros, M.1    Dyer, C.2    Smith, N.A.3
  • 7
    • 84964528874 scopus 로고    scopus 로고
    • A survey of longest common subsequence algorithms
    • Lasse Bergroth, Harri Hakonen, and Timo Raita. 2000. A survey of longest common subsequence algorithms. In Proc. of SPIRE.
    • (2000) Proc. of SPIRE
    • Bergroth, L.1    Hakonen, H.2    Raita, T.3
  • 8
    • 84926379949 scopus 로고    scopus 로고
    • Translating into morphologically rich languages with synthetic phrases
    • Victor Chahuneau, Eva Schlinger, Noah A. Smith, and Chris Dyer. 2013a. Translating into morphologically rich languages with synthetic phrases. In Proc. of EMNLP.
    • (2013) Proc. of EMNLP
    • Chahuneau, V.1    Schlinger, E.2    Smith, N.A.3    Dyer, C.4
  • 9
    • 84961288808 scopus 로고    scopus 로고
    • Knowledge-rich morphological priors for bayesian language models
    • Victor Chahuneau, Noah A Smith, and Chris Dyer. 2013b. Knowledge-rich morphological priors for bayesian language models. In Proc. of NAACL.
    • (2013) Proc. of NAACL
    • Chahuneau, V.1    Smith, N.A.2    Dyer, C.3
  • 12
    • 85094918571 scopus 로고    scopus 로고
    • Combining distributional and morphological information for part of speech induction
    • Alexander Clark. 2003. Combining distributional and morphological information for part of speech induction. In Proc. of EACL.
    • (2003) Proc. of EACL
    • Clark, A.1
  • 13
    • 84859033288 scopus 로고    scopus 로고
    • Combining morpheme-based machine translation with post-processing morpheme prediction
    • Ann Clifton and Anoop Sarkar. 2011. Combining morpheme-based machine translation with post-processing morpheme prediction. In Proc. of ACL.
    • (2011) Proc. of ACL
    • Clifton, A.1    Sarkar, A.2
  • 17
    • 84994144909 scopus 로고    scopus 로고
    • A joint model of orthography and morphological segmentation
    • Ryan Cotterell, Tim Vieria, and Hinrich Schütze. 2016. A joint model of orthography and morphological segmentation. In Proc. of NAACL.
    • (2016) Proc. of NAACL
    • Cotterell, R.1    Vieria, T.2    Schütze, H.3
  • 19
    • 80053262881 scopus 로고    scopus 로고
    • Discovering morphological paradigms from plain text using a dirichlet process mixture model
    • Markus Dreyer and Jason Eisner. 2011. Discovering morphological paradigms from plain text using a dirichlet process mixture model. In Proc. of EMNLP.
    • (2011) Proc. of EMNLP
    • Dreyer, M.1    Eisner, J.2
  • 20
    • 84905693352 scopus 로고    scopus 로고
    • Supervised learning of complete morphological paradigms
    • Greg Durrett and John DeNero. 2013. Supervised learning of complete morphological paradigms. In Proc. of NAACL.
    • (2013) Proc. of NAACL
    • Durrett, G.1    DeNero, J.2
  • 21
    • 85149140805 scopus 로고    scopus 로고
    • Parameter estimation for probabilistic finite-state transducers
    • Jason Eisner. 2002. Parameter estimation for probabilistic finite-state transducers. In Proc. of ACL.
    • (2002) Proc. of ACL
    • Eisner, J.1
  • 22
    • 84907370488 scopus 로고    scopus 로고
    • Modeling inflection and wordformation in SMT
    • Alexander Fraser, Marion Weller, Aoife Cahill, and Fabienne Cap. 2012. Modeling inflection and wordformation in SMT. In Proc. of EACL.
    • (2012) Proc. of EACL
    • Fraser, A.1    Weller, M.2    Cahill, A.3    Cap, F.4
  • 23
    • 80053246701 scopus 로고    scopus 로고
    • Improving statistical MT through morphological analysis
    • Sharon Goldwater and David McClosky. 2005. Improving statistical MT through morphological analysis. In Proc. of EMNLP, pages 676-683.
    • (2005) Proc. of EMNLP , pp. 676-683
    • Goldwater, S.1    McClosky, D.2
  • 24
    • 33749251046 scopus 로고    scopus 로고
    • Bidirectional lstm networks for improved phoneme classification and recognition
    • Alex Graves, Santiago Fernández, and Jürgen Schmidhuber. 2005. Bidirectional lstm networks for improved phoneme classification and recognition. In Proc. of ICANN.
    • (2005) Proc. of ICANN
    • Graves, A.1    Fernández, S.2    Schmidhuber, J.3
  • 25
    • 84953873103 scopus 로고    scopus 로고
    • Generating sequences with recurrent neural networks
    • Alex Graves. 2013. Generating sequences with recurrent neural networks. CoRR, abs/1308.0850.
    • (2013) CoRR
    • Graves, A.1
  • 31
    • 84878203695 scopus 로고
    • Regular models of phonological rule systems
    • Ronald M Kaplan and Martin Kay. 1994. Regular models of phonological rule systems. Computational linguistics, 20(3):331-378.
    • (1994) Computational Linguistics , vol.20 , Issue.3 , pp. 331-378
    • Kaplan, R.M.1    Kay, M.2
  • 34
    • 84860527733 scopus 로고    scopus 로고
    • Generating complex morphology for machine translation
    • Einat Minkov, Kristina Toutanova, and Hisami Suzuki. 2007. Generating complex morphology for machine translation. In Proc. of ACL.
    • (2007) Proc. of ACL
    • Minkov, E.1    Toutanova, K.2    Suzuki, H.3
  • 35
    • 85017209408 scopus 로고    scopus 로고
    • An unsupervised method for uncovering morphological chains
    • Karthik Narasimhan, Regina Barzilay, and Tommi Jaakkola. 2015. An unsupervised method for uncovering morphological chains. TACL.
    • (2015) TACL
    • Narasimhan, K.1    Barzilay, R.2    Jaakkola, T.3
  • 36
    • 84960154310 scopus 로고    scopus 로고
    • Inflection generation as discriminative string transduction
    • Garrett Nicolai, Colin Cherry, and Grzegorz Kondrak. 2015. Inflection generation as discriminative string transduction. In Proc. of NAACL.
    • (2015) Proc. of NAACL
    • Nicolai, G.1    Cherry, C.2    Kondrak, G.3
  • 38
    • 0002692959 scopus 로고    scopus 로고
    • Error-tolerant finite-state recognition with applications to morphological analysis and spelling correction
    • Kemal Oflazer. 1996. Error-tolerant finite-state recognition with applications to morphological analysis and spelling correction. Computational Linguistics, 22(1):73-89.
    • (1996) Computational Linguistics , vol.22 , Issue.1 , pp. 73-89
    • Oflazer, K.1
  • 39
    • 33744981648 scopus 로고    scopus 로고
    • Learning stochastic edit distance: Application in handwritten character recognition
    • Jose Oncina and Marc Sebban. 2006. Learning stochastic edit distance: Application in handwritten character recognition. Pattern recognition, 39(9):1575-1587.
    • (2006) Pattern Recognition , vol.39 , Issue.9 , pp. 1575-1587
    • Oncina, J.1    Sebban, M.2
  • 40
    • 84858427034 scopus 로고    scopus 로고
    • Unsupervised morphological segmentation with log-linear models
    • Hoifung Poon, Colin Cherry, and Kristina Toutanova. 2009. Unsupervised morphological segmentation with log-linear models. In Proc. of NAACL.
    • (2009) Proc. of NAACL
    • Poon, H.1    Cherry, C.2    Toutanova, K.3
  • 41
    • 84946032010 scopus 로고    scopus 로고
    • Grapheme-to-phoneme conversion using long short-term memory recurrent neural networks
    • Kanishka Rao, Fuchun Peng, Hasim Sak, and Françoise Beaufays. 2015. Grapheme-to-phoneme conversion using long short-term memory recurrent neural networks. In Proc. of ICASSP.
    • (2015) Proc. of ICASSP
    • Rao, K.1    Peng, F.2    Sak, H.3    Beaufays, F.4
  • 42
    • 84994070679 scopus 로고    scopus 로고
    • Weighting finite-state transductions with neural context
    • Pushpendre Rastogi, Ryan Cotterell, and Jason Eisner. 2016. Weighting finite-state transductions with neural context. In Proc. of NAACL.
    • (2016) Proc. of NAACL
    • Rastogi, P.1    Cotterell, R.2    Eisner, J.3
  • 43
    • 84919796700 scopus 로고    scopus 로고
    • Learning character-level representations for part-of-speech tagging
    • Cicero D. Santos and Bianca Zadrozny. 2014. Learning character-level representations for part-of-speech tagging. In Proc. of ICML.
    • (2014) Proc. of ICML
    • Santos, C.D.1    Zadrozny, B.2
  • 44
    • 34047192804 scopus 로고    scopus 로고
    • Semimarkov conditional random fields for information extraction
    • Sunita Sarawagi and William W Cohen. 2004. Semimarkov conditional random fields for information extraction. In Proc. of NIPS.
    • (2004) Proc. of NIPS
    • Sarawagi, S.1    Cohen, W.W.2
  • 46
    • 0141589488 scopus 로고    scopus 로고
    • Srilm-an extensible language modeling toolkit
    • Andreas Stolcke. 2002. Srilm-an extensible language modeling toolkit. In Proc. of Interspeech.
    • (2002) Proc. of Interspeech
    • Stolcke, A.1
  • 47
    • 84928547704 scopus 로고    scopus 로고
    • Sequence to sequence learning with neural networks
    • Ilya Sutskever, Oriol Vinyals, and Quoc VV Le. 2014. Sequence to sequence learning with neural networks. In Proc. of NIPS.
    • (2014) Proc. of NIPS
    • Sutskever, I.1    Vinyals, O.2    Le, Q.V.V.3
  • 48
    • 84859911998 scopus 로고    scopus 로고
    • Applying morphology generation models to machine translation
    • Kristina Toutanova, Hisami Suzuki, and Achim Ruopp. 2008. Applying morphology generation models to machine translation. In Proc. of ACL, pages 514-522.
    • (2008) Proc. of ACL , pp. 514-522
    • Toutanova, K.1    Suzuki, H.2    Ruopp, A.3
  • 50
    • 33846976926 scopus 로고    scopus 로고
    • Multilingual noise-robust supervised morphological analysis using the wordframe model
    • Richard Wicentowski. 2004. Multilingual noise-robust supervised morphological analysis using the wordframe model. In Proc. of SIGPHON.
    • (2004) Proc. of SIGPHON
    • Wicentowski, R.1
  • 51
    • 84994115437 scopus 로고    scopus 로고
    • Sequence-to-sequence neural net models for grapheme-to-phoneme conversion
    • Kaisheng Yao and Geoffrey Zweig. 2015. Sequence-to-sequence neural net models for grapheme-to-phoneme conversion. In Proc. of ICASSP.
    • (2015) Proc. of ICASSP
    • Yao, K.1    Zweig, G.2
  • 52
    • 85149142297 scopus 로고    scopus 로고
    • Minimally supervised morphological analysis by multimodal alignment
    • David Yarowsky and Richard Wicentowski. 2000. Minimally supervised morphological analysis by multimodal alignment. In Proc. of ACL.
    • (2000) Proc. of ACL
    • Yarowsky, D.1    Wicentowski, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.