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Hits 1 – 3 of 3
1
Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model ...
Mielke, Sabrina J.
;
Eisner, Jason
. - : arXiv, 2018
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2
Are All Languages Equally Hard to Language-Model? ...
Cotterell, Ryan
;
Mielke, Sabrina J.
;
Eisner, Jason
. - : arXiv, 2018
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3
Unsupervised Disambiguation of Syncretism in Inflected Lexicons ...
Cotterell, Ryan
;
Kirov, Christo
;
Mielke, Sabrina J.
;
Eisner, Jason
. - : arXiv, 2018
Abstract:
Lexical ambiguity makes it difficult to compute various useful statistics of a corpus. A given word form might represent any of several morphological feature bundles. One can, however, use unsupervised learning (as in EM) to fit a model that probabilistically disambiguates word forms. We present such an approach, which employs a neural network to smoothly model a prior distribution over feature bundles (even rare ones). Although this basic model does not consider a token's context, that very property allows it to operate on a simple list of unigram type counts, partitioning each count among different analyses of that unigram. We discuss evaluation metrics for this novel task and report results on 5 languages. ... : Published at NAACL 2018 ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/1806.03740
https://dx.doi.org/10.48550/arxiv.1806.03740
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