Emotion preservation in translation: Evaluating datasets for annotation projection

Kaisla Kajava, Emily Öhman, Piao Hui, Jörg Tiedemann

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper is a pilot study that aims to explore the viability of annotation projection from one language to another as well as to evaluate the multilingual data set we have created for emotion analysis. We study different language pairs based on parallel corpora for sentiment and emotion annotations and explore annotator agreement. We show that the data source is a possible one for reliable L1 data to be used in annotation projection from high-resource languages, such as English, into low-resource languages and that this is a reliable way of creating data sets for fine-grained sentiment analysis and emotion detection.

Original languageEnglish
Pages (from-to)38-50
Number of pages13
JournalCEUR Workshop Proceedings
Volume2612
Publication statusPublished - 2020
Externally publishedYes
Event5th Conference on Digital Humanities in the Nordic Countries, DHN 2020 - Riga, Latvia
Duration: 2020 Oct 212020 Oct 23

Keywords

  • Annotation Projection
  • Sentiment Analysis
  • Translation Studies

ASJC Scopus subject areas

  • Computer Science(all)

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