Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging.

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10194631" target="_blank" >RIV/00216208:11320/13:10194631 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging.
Original language description
Bilingual corpora offer a promising bridge between resource-rich and resource-poor languages, enabling the development of natural language processing systems for the latter. English is often selected as the resource-rich language, but another choice might give better performance. In this paper, we consider the task of unsupervised cross-lingual POS tagging, and construct a model that predicts the best source language for a given target language. In experiments on 9 languages, this model improves on using a single fixed source language. We then show that further improvements can be made by combining information from multiple source languages.
Czech name
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Czech description
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 6th International Joint Conference on Natural Language Processing
ISBN
978-4-9907348-0-0
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1243-1249
Publisher name
Asian Federation of Natural Language Processing
Place of publication
Nagoya, Japan
Event location
Nagoya, Japan
Event date
Oct 14, 2013
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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