This paper presents a machine translation architecture which hybridizes Matxin, a rulebased system, with regular phrase-based Statistical Machine Translation. In short, the hybrid translation process is guided by the rulebased engine and, before transference, a set of partial candidate translations provided by SMT subsystems is used to enrich the treebased representation. The final hybrid translation is created by choosing the most probable combination among the available fragments with a statistical decoder in a monotonic way.
We have applied the hybrid model to a pair
of distant languages, Spanish and Basque, and
according to our evaluation (both automatic
and manual) the hybrid approach significantly
outperforms the best SMT system on out-of-domain data.
CitationEspaña-Bonet, C. [et al.]. Hybrid machine translation guided by a rule-based system. A: Machine Translation Summit. "Machine translation summit XIII: proceedings of the 13th machine translation summit, September 19-23, 2011, Xiamen, China". Xiamen: 2011, p. 554-561.
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