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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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63 |
Annotation Guidelines for Arabic Nominal Gender, Number, and Rationality ...
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64 |
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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71 |
Can Automatic Post-Editing Make MT More Meaningful?
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Abstract:
Automatic post-editors (APEs) enable the re-use of black box machine translation (MT) systems for a variety of tasks where different aspects of translation are important. In this paper, we describe APEs that target adequacy errors, a critical problem for tasks such as cross-lingual question-answering, and compare different approaches for post-editing: a rule-based system and a feedback approach that uses a computer in the loop to suggest improvements to the MT system. We test the APEs on two different MT systems and across two different genres. Human evaluation shows that the APEs significantly improve adequacy, regardless of approach, MT system or genre: 30-56% of the post-edited sentences have improved adequacy compared to the original MT.
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Keyword:
Computer science; Linguistics
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URL: https://doi.org/10.7916/D80V8N4B
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74 |
Dialectal to Standard Arabic Paraphrasing to Improve Arabic-English Statistical Machine Translation
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75 |
Conventional Orthography for Dialectal Arabic (CODA) Version 0.1 ““ July 2011
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76 |
Conventional Orthography for Dialectal Arabic (CODA) Version 0.1 ““ July 2011 ...
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77 |
Dialectal to Standard Arabic Paraphrasing to Improve Arabic-English Statistical Machine Translation ...
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80 |
Automatic Identification of Errors in Arabic Handwriting Recognition
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