About: Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging.     Goto   Sponge   NotDistinct   Permalink

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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.
  • 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. (en)
Title
  • Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging.
  • Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging. (en)
skos:prefLabel
  • Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging.
  • Increasing the quality and quantity of source language data for unsupervised cross-lingual POS tagging. (en)
skos:notation
  • RIV/00216208:11320/13:10194631!RIV14-GA0-11320___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GBP103/12/G084)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 79505
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/13:10194631
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • tagging; lingual; cross; unsupervised; data; language; source; quantity; quality; increasing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [517EDADB7649]
http://linked.open...v/mistoKonaniAkce
  • Nagoya, Japan
http://linked.open...i/riv/mistoVydani
  • Nagoya, Japan
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 6th International Joint Conference on Natural Language Processing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Pecina, Pavel
  • Bird, Steven
  • Cook, Paul
  • Duong, Long Thanh
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Asian Federation of Natural Language Processing
https://schema.org/isbn
  • 978-4-9907348-0-0
http://localhost/t...ganizacniJednotka
  • 11320
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