Interactive Post-Editing for Verbosity Controlled Translation
Prabhakar Gupta, Anil Nelakanti, Grant M. Berry, Abhishek Sharma
Abstract
We explore Interactive Post-Editing (IPE) models for human-in-loop translation to help correct translation errors and rephrase it with a desired style variation. We specifically study verbosity for style variations and build on top of multi-source transformers that can read source and hypothesis to improve the latter with user inputs. Token-level interaction inputs for error corrections and length interaction inputs for verbosity control are used by the model to generate a suitable translation. We report BERTScore to evaluate semantic quality with other relevant metrics for translations from English to German, French and Spanish languages. Our model achieves superior BERTScore over state-of-the-art machine translation models while maintaining the desired token-level and verbosity preference.- Anthology ID:
- 2022.coling-1.454
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 5119–5128
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.454
- DOI:
- Bibkey:
- Cite (ACL):
- Prabhakar Gupta, Anil Nelakanti, Grant M. Berry, and Abhishek Sharma. 2022. Interactive Post-Editing for Verbosity Controlled Translation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5119–5128, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Interactive Post-Editing for Verbosity Controlled Translation (Gupta et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.454.pdf
- Data
- OPUS-MT
Export citation
@inproceedings{gupta-etal-2022-interactive, title = "Interactive Post-Editing for Verbosity Controlled Translation", author = "Gupta, Prabhakar and Nelakanti, Anil and Berry, Grant M. and Sharma, Abhishek", editor = "Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky, James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and Donatelli, Lucia and Ji, Heng and Kurohashi, Sadao and Paggio, Patrizia and Xue, Nianwen and Kim, Seokhwan and Hahm, Younggyun and He, Zhong and Lee, Tony Kyungil and Santus, Enrico and Bond, Francis and Na, Seung-Hoon", booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "International Committee on Computational Linguistics", url = "https://aclanthology.org/2022.coling-1.454", pages = "5119--5128", abstract = "We explore Interactive Post-Editing (IPE) models for human-in-loop translation to help correct translation errors and rephrase it with a desired style variation. We specifically study verbosity for style variations and build on top of multi-source transformers that can read source and hypothesis to improve the latter with user inputs. Token-level interaction inputs for error corrections and length interaction inputs for verbosity control are used by the model to generate a suitable translation. We report BERTScore to evaluate semantic quality with other relevant metrics for translations from English to German, French and Spanish languages. Our model achieves superior BERTScore over state-of-the-art machine translation models while maintaining the desired token-level and verbosity preference.", }
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%0 Conference Proceedings %T Interactive Post-Editing for Verbosity Controlled Translation %A Gupta, Prabhakar %A Nelakanti, Anil %A Berry, Grant M. %A Sharma, Abhishek %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F gupta-etal-2022-interactive %X We explore Interactive Post-Editing (IPE) models for human-in-loop translation to help correct translation errors and rephrase it with a desired style variation. We specifically study verbosity for style variations and build on top of multi-source transformers that can read source and hypothesis to improve the latter with user inputs. Token-level interaction inputs for error corrections and length interaction inputs for verbosity control are used by the model to generate a suitable translation. We report BERTScore to evaluate semantic quality with other relevant metrics for translations from English to German, French and Spanish languages. Our model achieves superior BERTScore over state-of-the-art machine translation models while maintaining the desired token-level and verbosity preference. %U https://aclanthology.org/2022.coling-1.454 %P 5119-5128
Markdown (Informal)
[Interactive Post-Editing for Verbosity Controlled Translation](https://aclanthology.org/2022.coling-1.454) (Gupta et al., COLING 2022)
- Interactive Post-Editing for Verbosity Controlled Translation (Gupta et al., COLING 2022)
ACL
- Prabhakar Gupta, Anil Nelakanti, Grant M. Berry, and Abhishek Sharma. 2022. Interactive Post-Editing for Verbosity Controlled Translation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5119–5128, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.