Abstract
In this article we present a syntax-based translation system, called TABL (Translation using Alignment-Based Learning). It translates natural language sentences by mapping grammar rules (which are induced by the Alignment-Based Learning grammatical inference framework) of the source language to those of the target language. By parsing a sentence in the source language, the grammar rules in the derivation are translated using the mapping and subsequently, a derivation in the target language is generated. The initial results are encouraging, illustrating that this is a valid machine translation approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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van Zaanen, M., Geertzen, J. (2006). Grammatical Inference for Syntax-Based Statistical Machine Translation. In: Sakakibara, Y., Kobayashi, S., Sato, K., Nishino, T., Tomita, E. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2006. Lecture Notes in Computer Science(), vol 4201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11872436_35
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DOI: https://doi.org/10.1007/11872436_35
Publisher Name: Springer, Berlin, Heidelberg
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