Overcoming statistical machine translation limitations: error analysis and proposed solutions for the Catalan–Spanish language pair |
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Authors: | Mireia Farrús Marta R Costa-jussà José B Mariño Marc Poch Adolfo Hernández Carlos Henríquez José A R Fonollosa |
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Affiliation: | 1.TALP Research Center, Department of Signal Theory and Communications,Universitat Politècnica de Catalunya,Barcelona,Spain;2.Office of Learning Technologies, Universitat Oberta de Catalunya,Barcelona,Spain;3.Voice and Language Department,Barcelona Media Innovation Center,Barcelona,Spain;4.Universitat Pompeu Fabra
,Barcelona,Spain |
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Abstract: | This work aims to improve an N-gram-based statistical machine translation system between the Catalan and Spanish languages,
trained with an aligned Spanish–Catalan parallel corpus consisting of 1.7 million sentences taken from El Periódico newspaper. Starting from a linguistic error analysis above this baseline system, orthographic, morphological, lexical, semantic
and syntactic problems are approached using a set of techniques. The proposed solutions include the development and application
of additional statistical techniques, text pre- and post-processing tasks, and rules based on the use of grammatical categories,
as well as lexical categorization. The performance of the improved system is clearly increased, as is shown in both human
and automatic evaluations of the system, with a gain of about 1.1 points BLEU observed in the Spanish-to-Catalan direction
of translation, and a gain of about 0.5 points in the reverse direction. The final system is freely available online as a
linguistic resource. |
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