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Neural fuzzy repair : integrating fuzzy matches into neural machine translation

Bram Bulté and Arda Tezcan (UGent)
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Abstract
We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.
Keywords
neural machine translation, translation memory, lt3

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Citation

Please use this url to cite or link to this publication:

MLA
Bulté, Bram, and Arda Tezcan. “Neural Fuzzy Repair : Integrating Fuzzy Matches into Neural Machine Translation.” 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), 2019, pp. 1800–09, doi:10.18653/v1/P19-1175.
APA
Bulté, B., & Tezcan, A. (2019). Neural fuzzy repair : integrating fuzzy matches into neural machine translation. 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), 1800–1809. https://doi.org/10.18653/v1/P19-1175
Chicago author-date
Bulté, Bram, and Arda Tezcan. 2019. “Neural Fuzzy Repair : Integrating Fuzzy Matches into Neural Machine Translation.” In 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), 1800–1809. https://doi.org/10.18653/v1/P19-1175.
Chicago author-date (all authors)
Bulté, Bram, and Arda Tezcan. 2019. “Neural Fuzzy Repair : Integrating Fuzzy Matches into Neural Machine Translation.” In 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), 1800–1809. doi:10.18653/v1/P19-1175.
Vancouver
1.
Bulté B, Tezcan A. Neural fuzzy repair : integrating fuzzy matches into neural machine translation. In: 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019). 2019. p. 1800–9.
IEEE
[1]
B. Bulté and A. Tezcan, “Neural fuzzy repair : integrating fuzzy matches into neural machine translation,” in 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), Florence, Italy, 2019, pp. 1800–1809.
@inproceedings{8624135,
  abstract     = {{We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.}},
  author       = {{Bulté, Bram and Tezcan, Arda}},
  booktitle    = {{57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019)}},
  isbn         = {{9781950737482}},
  keywords     = {{neural machine translation,translation memory,lt3}},
  language     = {{eng}},
  location     = {{Florence, Italy}},
  pages        = {{1800--1809}},
  title        = {{Neural fuzzy repair : integrating fuzzy matches into neural machine translation}},
  url          = {{http://doi.org/10.18653/v1/P19-1175}},
  year         = {{2019}},
}

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