Personalized machine translation: Preserving original author traits

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 languageEnglish
Title of host publicationLong Papers - Continued
PublisherAssociation for Computational Linguistics (ACL)
Pages1074-1084
Number of pages11
ISBN (Electronic)9781510838604
DOIs
StatePublished - 2017
Event15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia, Spain
Duration: 3 Apr 20177 Apr 2017

Publication series

Name15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference
Volume2

Conference

Conference15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
Country/TerritorySpain
CityValencia
Period3/04/177/04/17

Bibliographical note

Publisher Copyright:
© 2017 Association for Computational Linguistics.

ASJC Scopus subject areas

  • Linguistics and Language
  • Language and Linguistics

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