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Overview of the SPMRL 2013 Shared Task: A Cross-Framework Evaluation of Parsing Morphologically Rich Languages
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In: Proceedings of the Fourth Workshop on Statistical Parsing of Morphologically-Rich Languages ; https://hal.archives-ouvertes.fr/hal-00877096 ; Proceedings of the Fourth Workshop on Statistical Parsing of Morphologically-Rich Languages, Oct 2013, Seattle, Washington, United States. pp.146--182 (2013)
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62 |
LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual ...
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Annotation Guidelines for Arabic Nominal Gender, Number, and Rationality ...
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LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual ...
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Improved arabic-to-english statistical machine translation by reordering post-verbal subjects for word alignment
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Abstract:
We study challenges raised by the order of Arabic verbs and their subjects in statistical machine translation (SMT). We show that the boundaries of post-verbal subjects (VS) are hard to detect accurately, even with a state-of-the-art Arabic dependency parser. In addition, VS constructions have highly ambiguous reordering patterns when translated to English, and these patterns are very different for matrix (main clause) VS and non-matrix (subordinate clause) VS. Based on this analysis, we propose a novel method for leveraging VS information in SMT: we reorder VS constructions into pre-verbal (SV) order for word alignment. Unlike previous approaches to source-side reordering, phrase extraction and decoding are performed using the original Arabic word order. This strategy significantly improves BLEU and TER scores, even on a strong large-scale baseline. Limiting reordering to matrix VS yields further improvements.
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Keyword:
Computer science
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URL: https://doi.org/10.7916/D87S7ZSP
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Dialectal to Standard Arabic Paraphrasing to Improve Arabic-English Statistical Machine Translation
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Conventional Orthography for Dialectal Arabic (CODA) Version 0.1 ““ July 2011
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Conventional Orthography for Dialectal Arabic (CODA) Version 0.1 ““ July 2011 ...
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Dialectal to Standard Arabic Paraphrasing to Improve Arabic-English Statistical Machine Translation ...
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Automatic Identification of Errors in Arabic Handwriting Recognition
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