Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Alexander Erdmann"'
Autor:
Micha Elsner, Andrea D. Sims, Alexander Erdmann, Antonio Hernandez, Evan Jaffe, Lifeng Jin, Martha Booker Johnson, Shuan Karim, David L. King, Luana Lamberti Nunes, Byung-Doh Oh, Nathan Rasmussen, Cory Shain, Stephanie Antetomaso, Kendra V. Dickinson, Noah Diewald, Michelle McKenzie, Symon Stevens-Guille
Publikováno v:
Journal of Language Modelling, Vol 7, Iss 1, Pp 53–98-53–98 (2019)
We survey research using neural sequence-to-sequence models as compu- tational models of morphological learning and learnability. We discuss their use in determining the predictability of inflectional exponents, in making predictions about language a
Externí odkaz:
https://doaj.org/article/14d50c3b348d4816913f8ae538f8e3ef
Autor:
Alexander Erdmann, Adam Wiemerslage, Arya D. McCarthy, Mans Hulden, Miikka Silfverberg, Garrett Nicolai, Katharina Kann, Manex Agirrezabal
Publikováno v:
Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology.
We describe the second SIGMORPHON shared task on unsupervised morphology: the goal of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering is to cluster word types from a raw text corpus into paradigms. To this end, we re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad93c150570d00d741d59f59483f1448
https://doi.org/10.18653/v1/2021.sigmorphon-1.8
https://doi.org/10.18653/v1/2021.sigmorphon-1.8
Publikováno v:
ACL
Lexica distinguishing all morphologically related forms of each lexeme are crucial to many language technologies, yet building them is expensive. We propose a frugal paradigm completion approach that predicts all related forms in a morphological para
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ebe6a090f4d0b16015c1c2908d33c9e
https://doi.org/10.18653/v1/2020.acl-main.733
https://doi.org/10.18653/v1/2020.acl-main.733
Publikováno v:
ACL
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
New York University Scholars
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
New York University Scholars
This work treats the paradigm discovery problem (PDP), the task of learning an inflectional morphological system from unannotated sentences. We formalize the PDP and develop evaluation metrics for judging systems. Using currently available resources,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e239ce650c24f6662ad32a14b9362df9
https://doi.org/10.18653/v1/2020.acl-main.695
https://doi.org/10.18653/v1/2020.acl-main.695
Autor:
Martha Booker Johnson, Lifeng Jin, Evan Jaffe, Cory Shain, Nathan Rasmussen, Kendra V. Dickinson, Shuan Karim, Byung-Doh Oh, Luana Lamberti Nunes, Noah Diewald, Alexander Erdmann, Symon Jory Stevens-Guille, Andrea D. Sims, Antonio Hernandez, Michelle McKenzie, David L. King, Stephanie Antetomaso, Micha Elsner
Publikováno v:
Journal of Language Modelling, Vol 7, Iss 1, Pp 53–98-53–98 (2019)
We survey research using neural sequence-to-sequence models as compu-tational models of morphological learning and learnability. We discusstheir use in determining the predictability of inflectional exponents, inmaking predictions about language acqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e72fa1d69843bcd69e6ffc77f0d5a1f
https://doi.org/10.15398/jlm.v7i1.244
https://doi.org/10.15398/jlm.v7i1.244
Autor:
Sophie Cohen-Bodénès, Micha Elsner, Marie-Catherine de Marneffe, Béatrice Joyeux-Prunel, Alexander Erdmann, David Joseph Wrisley, Benjamin Allen, Christopher Brown, Yukun Feng, Brian D. Joseph
Publikováno v:
NAACL-HLT (1)
Scholars in inter-disciplinary fields like the Digital Humanities are increasingly interested in semantic annotation of specialized corpora. Yet, under-resourced languages, imperfect or noisily structured data, and user-specific classification tasks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8858b8b553288527ae3bc2aa7ea6bb79
https://doi.org/10.18653/v1/n19-1231
https://doi.org/10.18653/v1/n19-1231
Publikováno v:
Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology.
We present de-lexical segmentation, a linguistically motivated alternative to greedy or other unsupervised methods, requiring only minimal language specific input. Our technique involves creating a small grammar of closed-class affixes which can be w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77b03178c387db8d99d8eaac814928a7
https://doi.org/10.18653/v1/w19-4214
https://doi.org/10.18653/v1/w19-4214
Publikováno v:
ACL (2)
Word embeddings are crucial to many natural language processing tasks. The quality of embeddings relies on large non-noisy corpora. Arabic dialects lack large corpora and are noisy, being linguistically disparate with no standardized spelling. We mak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca3b8f0fd53580395f98c4779f0606d8
https://doi.org/10.18653/v1/p18-2089
https://doi.org/10.18653/v1/p18-2089
Autor:
Nizar Habash, Alexander Erdmann
Publikováno v:
Proceedings of the Fifteenth Workshop on Computational Research in Phonetics, Phonology, and Morphology.
Morphologically rich languages are challenging for natural language processing tasks due to data sparsity. This can be addressed either by introducing out-of-context morphological knowledge, or by developing machine learning architectures that specif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2658b98c2373fc0c190b2320263d5fe
https://doi.org/10.18653/v1/w18-5806
https://doi.org/10.18653/v1/w18-5806
Publikováno v:
New York University Scholars
We present the second ever evaluated Arabic dialect-to-dialect machine translation effort, and the first to leverage external resources beyond a small parallel corpus. The subject has not previously received serious attention due to lack of naturally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88535ae60d9077cde3b064db8dec2a3f
