A Hybrid Approach for Deep Machine Translation
نویسندگان
چکیده
This paper presents a Hybrid Approach to Deep Machine Translation in the language direction from English to Bulgarian. The set-up uses preand post-processing modules as well as two-level transfer. The language resources that have been incorporated are: WordNets for both languages; a valency lexicon for Bulgarian; aligned parallel corpora. The architecture comprises a predominantly statistical component (factor-based SMT in Moses) with some focused rule-based elements. The experiments show promising results and room for further improvements within the MT architecture.
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تاریخ انتشار 2016