Deep Neural Networks at the Service of Multilingual Parallel Sentence Extraction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10390126" target="_blank" >RIV/00216208:11320/18:10390126 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Deep Neural Networks at the Service of Multilingual Parallel Sentence Extraction
Original language description
Wikipedia provides an invaluable source of parallel multilingual data, which are in high demand for various sorts of linguistic inquiry, including both theoretical and practical studies. We intro- duce a novel end-to-end neural model for large-scale parallel data harvesting from Wikipedia. Our model is language-independent, robust, and highly scalable. We use our system for collect- ing parallel German-English, French-English and Persian-English sentences. Human evaluations at the end show the strong performance of this model in collecting high-quality parallel data. We also propose a statistical framework which extends the results of our human evaluation to other language pairs. Our model also obtained a state-of-the-art result on the German-English dataset of BUCC 2017 shared task on parallel sentence extraction from comparable corpora.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of The 27th International Conference on Computational Linguistics
ISBN
978-4-87974-703-7
ISSN
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e-ISSN
neuvedeno
Number of pages
12
Pages from-to
1372-1383
Publisher name
ICCL
Place of publication
Sheffield, GB
Event location
Santa Fe, New Mexico, USA
Event date
Aug 20, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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