Personalized machine translation: Preserving original author traits

Ella Rabinovich; Shachar Mirkin; Raj Nath Patel; Lucia Specia; Shuly Wintner

doi:https://doi.org/10.18653/v1/e17-1101

Personalized machine translation: Preserving original author traits

Ella Rabinovich, Shachar Mirkin, Raj Nath Patel, Lucia Specia, Shuly Wintner

Department of Computer Science

University of Haifa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domainadaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation, thereby creating more personalized machine translation systems.

Original language	American English
Title of host publication	Long Papers - Continued
Publisher	Association for Computational Linguistics (ACL)
Pages	1074-1084
Number of pages	11
ISBN (Electronic)	9781510838604
DOIs	https://doi.org/10.18653/v1/e17-1101
State	Published - 2017
Event	15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia, Spain Duration: 3 Apr 2017 → 7 Apr 2017

Publication series

Name	15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference
Volume	2

Conference

Conference	15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
Country/Territory	Spain
City	Valencia
Period	3/04/17 → 7/04/17

All Science Journal Classification (ASJC) codes

Linguistics and Language
Language and Linguistics

Access to Document

https://doi.org/10.18653/v1/e17-1101

Cite this

Rabinovich, E., Mirkin, S., Patel, R. N., Specia, L., & Wintner, S. (2017). Personalized machine translation: Preserving original author traits. In Long Papers - Continued (pp. 1074-1084). (15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference; Vol. 2). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-1101

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title = "Personalized machine translation: Preserving original author traits",

abstract = "The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domainadaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation, thereby creating more personalized machine translation systems.",

author = "Ella Rabinovich and Shachar Mirkin and Patel, {Raj Nath} and Lucia Specia and Shuly Wintner",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics.; 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 ; Conference date: 03-04-2017 Through 07-04-2017",

year = "2017",

doi = "https://doi.org/10.18653/v1/e17-1101",

language = "American English",

series = "15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference",

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pages = "1074--1084",

booktitle = "Long Papers - Continued",

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}

Rabinovich, E, Mirkin, S, Patel, RN, Specia, L & Wintner, S 2017, Personalized machine translation: Preserving original author traits. in Long Papers - Continued. 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference, vol. 2, Association for Computational Linguistics (ACL), pp. 1074-1084, 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, 3/04/17. https://doi.org/10.18653/v1/e17-1101

Personalized machine translation: Preserving original author traits. / Rabinovich, Ella; Mirkin, Shachar; Patel, Raj Nath et al.
Long Papers - Continued. Association for Computational Linguistics (ACL), 2017. p. 1074-1084 (15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Specia, Lucia

AU - Wintner, Shuly

PY - 2017

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N2 - The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domainadaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation, thereby creating more personalized machine translation systems.

AB - The language that we produce reflects our personality, and various personal and demographic characteristics can be detected in natural language texts. We focus on one particular personal trait of the author, gender, and study how it is manifested in original texts and in translations. We show that author's gender has a powerful, clear signal in originals texts, but this signal is obfuscated in human and machine translation. We then propose simple domainadaptation techniques that help retain the original gender traits in the translation, without harming the quality of the translation, thereby creating more personalized machine translation systems.

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ER -

Rabinovich E, Mirkin S, Patel RN, Specia L, Wintner S. Personalized machine translation: Preserving original author traits. In Long Papers - Continued. Association for Computational Linguistics (ACL). 2017. p. 1074-1084. (15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference). doi: https://doi.org/10.18653/v1/e17-1101

Personalized machine translation: Preserving original author traits

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