This paper proposes a forest-based tree sequence to string translation model for syntaxbased statistical machine translation, which automatically learns tree sequence to string tr...
Hui Zhang, Min Zhang, Haizhou Li, AiTi Aw, Chew Li...
We propose a novel HMM-based framework to accurately transliterate unseen named entities. The framework leverages features in letteralignment and letter n-gram pairs learned from ...
Bing Zhao, Nguyen Bach, Ian R. Lane, Stephan Vogel
This paper addresses the problem of mining named entity translations from comparable corpora, specifically, mining English and Chinese named entity translation. We first observe...
Jinhan Kim, Long Jiang, Seung-won Hwang, Young-In ...
Recent work on the transfer of semantic information across languages has been recently applied to the development of resources annotated with Frame information for different non-En...
Roberto Basili, Diego De Cao, Danilo Croce, Bonave...
Statistical bilingual word alignment has been well studied in the context of machine translation. This paper adapts the bilingual word alignment algorithm to monolingual scenario ...