Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Patrik Lambert"'
Autor:
José B. Mariño, Rafael E. Banchs, Josep M. Crego, Adrià de Gispert, Patrik Lambert, José A. R. Fonollosa, Marta R. Costa-jussà
Publikováno v:
Computational Linguistics, Vol 32, Iss 4 (2021)
Externí odkaz:
https://doaj.org/article/c119f5e8d76043939cc5bedaf65b378a
Publikováno v:
Natural Language Engineering. :1-30
Deep neural networks as an end-to-end approach lack robustness from an application point of view, as it is very difficult to fix an obvious problem without retraining the model, for example, when a model consistently predicts positive when seeing the
Publikováno v:
ACL (2)
Attention based deep learning systems have been demonstrated to be the state of the art approach for aspect-level sentiment analysis, however, end-to-end deep neural networks lack flexibility as one can not easily adjust the network to fix an obvious
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 24:745-754
In this paper, we present information retrieval as a powerful tool for addressing an imperative problem in the field of statistical machine translation, i.e., improving translation quality when not enough parallel corpora are available. We devise a f
Autor:
Marta R. Costa-jussà, Reinhard Rapp, Patrik Lambert, Kurt Eberle, Rafael E. Banchs, Bogdan Babych
This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are
Autor:
Rafael E. Banchs, Reinhard Rapp, Kurt Eberle, Patrik Lambert, Marta R. Costa-juss, Bogdan Babych
Publikováno v:
Theory and Applications of Natural Language Processing ISBN: 9783319213101
Hybrid Approaches to Machine Translation
Hybrid Approaches to Machine Translation
This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::faa42ecddc20e08a5e94e91668186484
https://doi.org/10.1007/978-3-319-21311-8
https://doi.org/10.1007/978-3-319-21311-8
Publikováno v:
Machine Translation. 26:289-323
In most statistical machine translation (SMT) systems, bilingual segments are extracted via word alignment. However, there is a need for systematic study as to what alignment characteristics can benefit MT under specific experimental settings such as
Autor:
Patrik Lambert
Publikováno v:
ACL (2)
Most cross-lingual sentiment classification (CLSC) research so far has been performed at sentence or document level. Aspect-level CLSC, which is more appropriate for many applications, presents the additional difficulty that we consider subsentential
Publikováno v:
Language Resources and Evaluation. 39:267-285
The purpose of this paper is to provide guidelines for building a word alignment evaluation scheme. The notion of word alignment quality depends on the application: here we review standard scoring metrics for full text alignment and give explanations
Autor:
Louis Taillefer, Patrick Fournier, Christian Lupien, Patrik Lambert, May Chiao, Robert W. Hill, Robert Gagnon
Publikováno v:
Physical Review B. 62:3554-3558
A residual linear term is observed in the thermal conductivity of optimally-doped Bi-2212 at very low temperatures whose magnitude is in excellent agreement with the value expected from Fermi-liquid theory and the d-wave energy spectrum measured by p