@inproceedings{2eb297c1bb9b4f3a8ddad46a3cf88b20,
title = "A purely monotonic approach to machine translation for similar languages",
abstract = "This paper investigates the effect of taking a strictly monotonic approach to machine translation for a restricted set of suitable language pairs. We studied the effect of decoding monotonically for a set of language pairs which has similar word order characteristics and found that for some language pairs - namely language pairs where both languages are in SOV order - there was almost no difference in machine translation quality. The results of this experiment motivated the extension of the monotonic approach into the alignment stage of the training. We used a Bayesian non-parametric aligner that has been shown to out-perform GIZA++ in combination with the grow-diag-final- and heuristic on transliteration data. Our results show that the monotonic aligner was able to match the performance of the GIZA++ baseline, and gains in translation performance were obtained by integrating both aligners into the systems.",
keywords = "bilingual alignment, machine translation, monotonic decoding",
author = "Thu, {Ye Kyaw} and Andrew Finch and Eiichiro Sumita and Yoshinori Sagisaka",
year = "2013",
doi = "10.1109/IALP.2013.31",
language = "English",
isbn = "9780769550633",
series = "Proceedings - 2013 International Conference on Asian Language Processing, IALP 2013",
pages = "107--110",
booktitle = "Proceedings - 2013 International Conference on Asian Language Processing, IALP 2013",
note = "2013 International Conference on Asian Language Processing, IALP 2013 ; Conference date: 17-08-2013 Through 19-08-2013",
}