USAAR-SAPE: An English–Spanish Statistical Automatic Post-Editing System
By Santanu Pal, Mihaela Vela, Sudip Kumar Naskar, Josef van Genabith. 2015
17 citations recorded by the source corpus.
We describe the USAAR-SAPE English‐ Spanish Automatic Post-Editing (APE) system submitted to the APE Task organized in the Workshop on Statistical Machine Translation (WMT) in 2015. Our system was able to improve upon the baseline MT system output by incorporating Phrase-Based Statistical MT (PBSMT) technique into the monolingual Statistical APE task (SAPE). The reported final submission crucially involves hybrid word alignment. The SAPE system takes raw Spanish Machine Translation (MT) output provided by the shared task organizers and produces post-edited Spanish text. The parallel data consist of English Text, raw machine translated Spanish output, and their corresponding manually post-edited versions. The major goal of the task is to reduce the post-editing effort by improving the quality of the MT output in terms of fluency and adequacy.
Subfields: Artificial Intelligence, Molecular Biology, Natural Language Processing
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- Ondrej Bojar
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In Molecular Biology
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Citations in the corpus
- Findings of the 2016 Conference on Machine Translation (2016, methodology): “The statistical APE component is based on the phrase-based APE approach of Pal et al. (2015). MT outputs generally contain four types of errors: presence of unwarranted words, wrong word surface form, absence of some relevant words, and wrong word order.”
- USAAR: An Operation Sequential Model for Automatic Statistical Post-Editing (2016, methodology): “…a powerful translation mechanism which can directly be modelled to a phrase-based SAPE (PB-SAPE) system (Simard et al., 2007a; Simard et al., 2007b; Pal et al., 2015) using target language MT output ( T L MT ) and their corresponding post-edited version ( T L PE ) as a parallel training corpus.”