DE eng

Search in the Catalogues and Directories

Page: 1 2
Hits 1 – 20 of 21

1
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Association for Computational Linguistics, 2021
BASE
Show details
2
Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : Association for Computational Linguistics, 2020
BASE
Show details
3
The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ...
BASE
Show details
4
The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ...
BASE
Show details
5
Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian ...
BASE
Show details
6
Fine-grained human evaluation of neural versus phrase-based machine translation ...
BASE
Show details
7
A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions ...
BASE
Show details
8
Assisting non-expert speakers of under-resourced languages in assigning stems and inflectional paradigms to new word entries of morphological dictionaries
Forcada, Mikel L.; Carrasco, Rafael C.; Pérez-Ortiz, Juan Antonio. - : Springer Science+Business Media Dordrecht, 2017
BASE
Show details
9
Fine-Grained Human Evaluation of Neural Versus Phrase-Based Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 121-132 (2017) (2017)
Abstract: We compare three approaches to statistical machine translation (pure phrase-based, factored phrase-based and neural) by performing a fine-grained manual evaluation via error annotation of the systems’ outputs. The error types in our annotation are compliant with the multidimensional quality metrics (MQM), and the annotation is performed by two annotators. Inter-annotator agreement is high for such a task, and results show that the best performing system (neural) reduces the errors produced by the worst system (phrase-based) by 54%.
Keyword: Computational linguistics. Natural language processing; P98-98.5
URL: https://doi.org/10.1515/pralin-2017-0014
https://doaj.org/article/b4e1fd45807c4747bcc465fbf853507b
BASE
Hide details
10
Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical Machine Translation
BASE
Show details
11
RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
BASE
Show details
12
RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 106, Iss 1, Pp 193-204 (2016) (2016)
BASE
Show details
13
A generalised alignment template formalism and its application to the inference of shallow-transfer machine translation rules from scarce bilingual corpora
BASE
Show details
14
An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation
BASE
Show details
15
Choosing the correct paradigm for unknown words in rule-based machine translation systems
BASE
Show details
16
The Universitat d’Alacant hybrid machine translation system for WMT 2011
Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Association for Computational Linguistics, 2011
BASE
Show details
17
Integrating shallow-transfer rules into phrase-based statistical machine translation
BASE
Show details
18
Enriching a statistical machine translation system trained on small parallel corpora with rule-based bilingual phrases
BASE
Show details
19
A Widely Used Machine Translation Service and its Migration to a Free/Open-Source Solution : the Case of Softcatalà
Sánchez-Cartagena, Víctor M.; Ivars-Ribes, Xavier. - : Universitat Oberta de Catalunya, 2011
BASE
Show details
20
ScaleMT: a free/open-source framework for building scalable machine translation web services
Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio. - : Charles University in Prague. Institute of Formal and Applied Linguistics, 2009. : Versita, 2009
BASE
Show details

Page: 1 2

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
21
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern