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Iterative, MT-based sentence alignment of parallel texts


Sennrich, R; Volk, M (2011). Iterative, MT-based sentence alignment of parallel texts. In: NODALIDA 2011, Nordic Conference of Computational Linguistics, Riga, 11 May 2011 - 13 May 2011.

Abstract

Recent research has shown that MT-based sentence alignment is a robust approach for noisy parallel texts.
However, using Machine Translation for sentence alignment causes a chicken-and-egg problem: to train a corpus-based MT system, we need sentence-aligned data, and MT-based sentence alignment depends on an MT system.
We describe a bootstrapping approach to sentence alignment that resolves this circular dependency by computing an initial alignment with length-based methods.
Our evaluation shows that iterative MT-based sentence alignment significantly outperforms widespread alignment approaches on our evaluation set, without requiring any linguistic resources other than the to-be-aligned bitext.

Abstract

Recent research has shown that MT-based sentence alignment is a robust approach for noisy parallel texts.
However, using Machine Translation for sentence alignment causes a chicken-and-egg problem: to train a corpus-based MT system, we need sentence-aligned data, and MT-based sentence alignment depends on an MT system.
We describe a bootstrapping approach to sentence alignment that resolves this circular dependency by computing an initial alignment with length-based methods.
Our evaluation shows that iterative MT-based sentence alignment significantly outperforms widespread alignment approaches on our evaluation set, without requiring any linguistic resources other than the to-be-aligned bitext.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:13 May 2011
Deposited On:10 May 2011 09:07
Last Modified:12 Aug 2017 10:15
Funders:Swiss National Science Foundation
Related URLs:http://www.lumii.lv/nodalida2011/home.html

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