NU HLT at CMCL 2022 Shared Task: Multilingual and Crosslingual Prediction of Human Reading Behavior in Universal Language Space

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

In this paper, we present a unified model that works for both multilingual and crosslingual prediction of reading times of words in various languages. The secret behind the success of this model is in the preprocessing step where all words are transformed to their universal language representation via the International Phonetic Alphabet (IPA). To the best of our knowledge, this is the first study to favorably exploit this phonological property of language for the two tasks. Various feature types were extracted covering basic frequencies, n-grams, information theoretic, and psycholinguistically-motivated predictors for model training. A finetuned Random Forest model obtained best performance for both tasks with 3.8031 and 3.9065 MAE scores for mean first fixation duration (FFDAvg) and mean total reading time (TRTAvg) respectively.

Original languageEnglish
Title of host publicationCMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop
EditorsEmmanuele Chersoni, Nora Hollenstein, Cassandra L. Jacobs, Yohei Oseki, Laurent Prevot, Enrico Santus
PublisherAssociation for Computational Linguistics (ACL)
Pages108-113
Number of pages6
ISBN (Electronic)9781955917292
Publication statusPublished - 31 Dec 2022
Event12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022 - Dublin, Ireland
Duration: 26 May 2022 → …

Publication series

NameCMCL 2022 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings of the Workshop

Conference

Conference12th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2022
Country/TerritoryIreland
CityDublin
Period26/05/22 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Artificial Intelligence
  • Software
  • Linguistics and Language

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