Controlling Politeness in Neural Machine Translation via Side Constraints

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many languages use honorifics to express politeness, social distance, or the relative social status between the speaker and their addressee(s). In machine translation from a language without honorifics such as English, it is difficult to predict the appropriate honorific, but users may want to control the level of politeness in the output. In this paper, we perform a pilot study to control honorifics in neural machine translation (NMT) via side constraints, focusing on English!German. We show that by marking up the (English) source side of the training data with a feature that encodes the use of honorifics on the (German) target side, we can control the honorifics produced at test time. Experiments show that the choice of honorifics has a big impact on translation quality as measured by BLEU, and oracle experiments show that substantial improvements are possible by constraining the translation to the desired level of politeness.
Original languageEnglish
Title of host publicationThe 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2016)
Place of PublicationSan Diego, California
PublisherAssociation for Computational Linguistics
Pages35-40
Number of pages6
DOIs
Publication statusPublished - Jun 2016
Event15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - San Diego, United States
Duration: 12 Jun 201617 Jun 2016
http://naacl.org/naacl-hlt-2016/
http://naacl.org/naacl-hlt-2016/

Conference

Conference15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Abbreviated titleNAACL HLT 2016
CountryUnited States
CitySan Diego
Period12/06/1617/06/16
Internet address

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