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Erschienen in:
An Automatic Approach for WordNet Enrichment Applied to Arabic WordNet Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

A POS-Based Preordering Approach for English-to-Arabic Statistical Machine Translation

verfasst von : Mohamed Seghir Hadj Ameur, Ahmed Guessoum, Farid Meziane

Erschienen in: Arabic Language Processing: From Theory to Practice

Verlag: Springer International Publishing

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Abstract

In this work, we present a POS-based preordering approach that tackles both long- and short-distance reordering phenomena. Syntactic unlexicalized reordering rules are automatically extracted from a parallel corpus using only word alignment and a source-side language tagging. The reordering rules are used in a deterministic manner; this prevents the decoding speed from being bottlenecked in the reordering procedure. A new approach for both rule filtering and rule application is used to ensure a fast and efficient reordering. The tests performed on the IWSLT2016 English-to-Arabic evaluation benchmark show a noticeable increase in the overall Blue Score for our system over the baseline PSMT system.

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Vorheriges Kapitel Word Embedding-Based Approaches for Measuring Semantic Similarity of Arabic-English Sentences
Nächstes Kapitel Towards a High-Quality Lemma-Based Text to Speech System for the Arabic Language
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FindCS is a simple method that finds the number of crossing alignments (CS) for a given aligned sentence.
 
3
 
5
We mean by a monotonic corpus, a corpus in which the alignment does not contain any crossing links.
 
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Metadaten
Titel
A POS-Based Preordering Approach for English-to-Arabic Statistical Machine Translation
verfasst von
Mohamed Seghir Hadj Ameur
Ahmed Guessoum
Farid Meziane
Copyright-Jahr
2018
Buch
Arabic Language Processing: From Theory to Practice

Print ISBN: 978-3-319-73499-6

Electronic ISBN: 978-3-319-73500-9

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-73500-9_3