Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Thai Phuong Nguyen"'
Publikováno v:
Analytical and bioanalytical chemistry. 409(25)
In this work, we develop an aerosol-based, time-resolved ion mobility-coupled mass characterization method to investigate colloidal assembly of graphene oxide (GO)-silver nanoparticle (AgNP) hybrid nanostructure on a quantitative basis. Transmission
Autor:
Thai Phuong Nguyen1 thai@jaist.ac.jp, Akira Shimazu2 shimazu@jaist.ac.jp, Minh Le Nguyen2 nguyenml@jaist.ac.jp, Vinh Van Nguyen2 vinhnv@jaist.ac.jp
Publikováno v:
International Journal of Computer Processing of Oriental Languages. Jun2007, Vol. 20 Issue 2/3, p79-99. 21p. 5 Diagrams, 13 Charts.
Publikováno v:
Procedia - Social and Behavioral Sciences. 27:77-85
In this paper, we present a reordering model based on Maximum Entropy with local and non-local features. This model is extended from a hierarchical reordering model with PBSMT [1], which integrates rich syntactic information directly in decoder as lo
Autor:
Akira Shimazu, Thai Phuong Nguyen
Publikováno v:
Machine Translation. 20:147-166
We present a phrase-based statistical machine translation approach which uses linguistic analysis in the preprocessing phase. The linguistic analysis includes morphological transformation and syntactic transformation. Since the word-order problem is
Publikováno v:
International Journal of Computer Processing of Languages. 20:79-99
We describe a syntactic transformation model based on the probabilistic context-free grammar. This model is trained by using bilingual corpus and a broad coverage parser of the source language. Then we present two methods to solve the word-order prob
Akademický článek
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Publikováno v:
CoNLL
Though phrase-based SMT has achieved high translation quality, it still lacks of generalization ability to capture word order differences between languages. In this paper we describe a general method for tree-to-string phrase-based SMT. We study how
Publikováno v:
Advances in Natural Language Processing ISBN: 9783540852865
GoTAL
GoTAL
This paper presents a new method for reordering in phrase based statistical machine translation (PBSMT). Our method is based on previous chunk-level reordering methods for PBSMT. Our method is a global reordering. First, we parse the source language
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a19a74e28fae4044616eefccec43029
https://doi.org/10.1007/978-3-540-85287-2_45
https://doi.org/10.1007/978-3-540-85287-2_45
Publikováno v:
RIVF
The paper presents a new method for reordering in phrase based statistical machine translation (PBMT). Our method is based on previous chunk-level reordering methods for PBMT. First, we parse the source language sentence to a chunk tree, according to
Akademický článek
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