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NAACL
2007

Joint Morphological-Lexical Language Modeling for Machine Translation

9 years 3 months ago
Joint Morphological-Lexical Language Modeling for Machine Translation
We present a joint morphological-lexical language model (JMLLM) for use in statistical machine translation (SMT) of language pairs where one or both of the languages are morphologically rich. The proposed JMLLM takes advantage of the rich morphology to reduce the Out-Of-Vocabulary (OOV) rate, while keeping the predictive power of the whole words. It also allows incorporation of additional available semantic, syntactic and linguistic information about the morphemes and words into the language model. Preliminary experiments with an English to Dialectal-Arabic SMT system demonstrate improved translation performance over trigram based baseline language model.
Ruhi Sarikaya, Yonggang Deng
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NAACL
Authors Ruhi Sarikaya, Yonggang Deng
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