A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese

  • Leandro Borges dos SantosEmail author
  • Magali Sanches Duran
  • Nathan Siegle Hartmann
  • Arnaldo CandidoJr.
  • Gustavo Henrique Paetzold
  • Sandra Maria Aluisio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10415)


Psycholinguistic properties of words have been used in various approaches to Natural Language Processing tasks, such as text simplification and readability assessment. Most of these properties are subjective, involving costly and time-consuming surveys to be gathered. Recent approaches use the limited datasets of psycholinguistic properties to extend them automatically to large lexicons. However, some of the resources used by such approaches are not available to most languages. This study presents a method to infer psycholinguistic properties for Brazilian Portuguese (BP) using regressors built with a light set of features usually available for less resourced languages: word length, frequency lists, lexical databases composed of school dictionaries and word embedding models. The correlations between the properties inferred are close to those obtained by related works. The resulting resource contains 26,874 words in BP annotated with concreteness, age of acquisition, imageability and subjective frequency.


Psycholinguistic properties Brazilian Portuguese Lexical resources 



This work was supported by CNPq and FAPESP.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Leandro Borges dos Santos
    • 1
    Email author
  • Magali Sanches Duran
    • 1
  • Nathan Siegle Hartmann
    • 1
  • Arnaldo CandidoJr.
    • 2
  • Gustavo Henrique Paetzold
    • 3
  • Sandra Maria Aluisio
    • 1
  1. 1.Institute of Mathematics and Computer SciencesUniversity of São PauloSão PauloBrazil
  2. 2.Federal Technological University of Paraná (UTFPR), MedianeiraMedianeiraBrazil
  3. 3.Department of Computer ScienceUniversity of SheffieldSheffieldEngland

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