• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Lowry, Cass (2)
    • Callejas, Francesca (1)
    • Chodorow, Martin (1)
    • Eskander, Ramy (1)
    • Khandagale, Sujay (1)
    • Klavans, Judith (1)
    • Lowry, Cass [Verfasser] (1)
    • Madsen, Christen N (1)
    • Madsen, Christen N. [Verfasser] (1)
    • Martohardjono, Gita (1)
    •   more
  • 
    Year
  • 
    Medium
  • 
    Type
  • 
    BLLDB-Access

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 Minimally-Supervised Morphological Segmentation using Adaptor Grammars with Linguistic Priors ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Callejas, Francesca; Eskander, Ramy; Khandagale, Sujay; Klavans, Judith; Lowry, Cass; Muresan, Smaranda; Polinsky, polinsky@umd.edu. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.347 Abstract: With the increasing interest in low-resource languages, unsupervised morphological segmentation has become an active area of research, where approaches based on Adaptor Grammars achieve state-of-the-art results. We demonstrate the power of harnessing linguistic knowledge as priors within Adaptor Grammars in a minimally-supervised learning fashion. We introduce two types of priors: 1) grammar definition, where we design language-specific grammars; and 2) linguist-provided affixes, collected by an expert in the language and seeded into the grammars. We use Japanese and Georgian as respective case studies for the two types of priors and introduce new datasets for these languages, with gold morphological segmentation for evaluation. We show that the use of priors results in error reductions of 8.9% and 34.2%, respectively, over the equivalent state-of-the-art unsupervised system. ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Morphology; Neural Network; Semantics URL: https://dx.doi.org/10.48448/j68h-8888 https://underline.io/lecture/26438-minimally-supervised-morphological-segmentation-using-adaptor-grammars-with-linguistic-priors BASE Hide details 2 Language history attenuates syntactic prediction in L1 processing [<Journal>] Stern, Michael C. [Verfasser]; Madsen, Christen N. [Verfasser]; Stover, LeeAnn M. [Verfasser]. DNB Subject Category Language Show details 3 TASK-EVOKED PUPILLARY RESPONSES (TEPR) IN SPANISH-ENGLISH BILINGUALS' PROCESSING OF RELATIVE CLAUSES ... Madsen, Christen N; Martohardjono, Gita; Lowry, Cass. - : Unpublished, 2019 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 1 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 2 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0