Studying the Role of Named Entities for Content Preservation in Text Style Transfer

Nikolay Babakov, David Dale, Varvara Logacheva, Irina Krotova, Alexander Panchenko

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Text style transfer techniques are gaining popularity in Natural Language Processing, finding various applications such as text detoxification, sentiment, or formality transfer. However, the majority of the existing approaches were tested on such domains as online communications on public platforms, music, or entertainment yet none of them were applied to the domains which are typical for task-oriented production systems, such as personal plans arrangements (e.g. booking of flights or reserving a table in a restaurant). We fill this gap by studying formality transfer in this domain. We noted that, the texts in this domain are full of named entities, which are very important for keeping the original sense of the text. Indeed, if for example, someone communicates destination city of a flight is must not be altered. Thus, we concentrate on the role of named entities in content preservation for formality text style transfer. We collect a new dataset for the evaluation of content similarity measures in text style transfer. It is taken from a corpus of task-oriented dialogues and contains many important entities related to realistic requests that make this dataset particularly useful for testing style transfer models before using them in production. Besides, we perform an error analysis of a pre-trained formality transfer model and introduce a simple technique to use information about named entities to enhance the performance of baseline content similarity measures used in text style transfer.

Original languageEnglish
Title of host publicationNatural Language Processing and Information Systems - 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, Proceedings
EditorsPaolo Rosso, Valerio Basile, Raquel Martínez, Elisabeth Métais, Farid Meziane
PublisherSpringer Science and Business Media Deutschland GmbH
Pages437-448
Number of pages12
ISBN (Print)9783031084720
DOIs
Publication statusPublished - 2022
Event27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022 - Valencia, Spain
Duration: 15 Jun 202217 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13286 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022
Country/TerritorySpain
CityValencia
Period15/06/2217/06/22

Keywords

  • Content preservation
  • Named entities
  • Text style transfer

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