A Bayesian model for joint word alignment and part-of-speech transfer

Robert Östling

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKirjan luku tai artikkeliTieteellinen

Abstrakti

Current methods for word alignment require considerable amounts of
parallel text to deliver accurate results, a requirement which is met only for
a small minority of the world's approximately 7,000 languages.
We show that by jointly performing word alignment and annotation transfer in
a novel Bayesian model, alignment accuracy can be
improved for language pairs where annotations are available for only
one of the languages---a finding which could facilitate the study and
processing of a vast number of low-resource languages.
We also present an evaluation where our method is used to perform
single-source and multi-source part-of-speech transfer with 22 translations
of the same text in four different languages. This allows us to quantify the
considerable variation in accuracy depending on the specific source text(s)
used, even with different translations into the same language.
Alkuperäiskielienglanti
OtsikkoProceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Sivumäärä10
JulkaisupaikkaOsaka, Japan
KustantajaThe Association for Computational Linguistics
Julkaisupäivä1 jouluk. 2016
Sivut620-629
ISBN (elektroninen)978-4-87974-702-0
TilaJulkaistu - 1 jouluk. 2016
OKM-julkaisutyyppiB2 Kirjan tai muun kokoomateoksen osa

Julkaisusarja

NimiProceedings of COLING
ISSN (painettu)1525-2477

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