LanideNN: Multilingual Language Identification on Character Window
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372159" target="_blank" >RIV/00216208:11320/17:10372159 - 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
LanideNN: Multilingual Language Identification on Character Window
Original language description
In language identification, a common first step in natural language processing, we want to automatically determine the language of some input text. Monolingual language identification assumes that the given document is written in one language. In multilingual language identification, the document is usually in two or three languages and we just want their names. We aim one step further and propose a method for textual language identification where languages can change arbitrarily and the goal is to identify the spans of each of the languages. Our method is based on Bidirectional Recurrent Neural Networks and it performs well in monolingual and multilingual language identification tasks on six datasets covering 131 languages. The method keeps the accuracy also for short documents and across domains, so it is ideal for off-the-shelf use without preparation of training data.
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<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
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 15th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers
ISBN
978-1-5108-3860-4
ISSN
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e-ISSN
neuvedeno
Number of pages
10
Pages from-to
927-936
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Valencia, Spain
Event date
Apr 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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