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Licensed Unlicensed Requires Authentication Published by De Gruyter January 14, 2020

Adolescent age estimation using voice features

  • Marcin D. Bugdol ORCID logo EMAIL logo , Monika N. Bugdol ORCID logo , Maria J. Bieńkowska , Anna Lipowicz , Agata M. Wijata and Andrzej W. Mitas


In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording. Voice recordings were supplemented with height measurement in order to check if it could improve the accuracy of the proposed solution. Predictor selection was performed using the LASSO (least absolute shrinkage and selection operator) algorithm. For age estimation, the random forest (RF) for regression method was employed and it was tested using a 10-fold cross-validation. The lowest absolute error (0.37 year ± 0.28) was obtained for boys only when all selected features were included into prediction. In all cases, the achieved accuracy was higher for boys than for girls, which results from the fact that the change of voice with age is larger for men than for women. The achieved results suggest that the presented approach can be employed for accurate age estimation during rapid development in children.


We would like to thank Bruce Turner for the English language corrections.

  1. Author Statement

  2. Research funding: Authors state no funding involved.

  3. Conflict of interest: Authors declare no conflict of interest.

  4. Informed consent: Informed consent is not applicable.

  5. Ethical approval: The conducted research is not related to either human or animal use.


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Received: 2018-05-19
Accepted: 2019-11-11
Published Online: 2020-01-14
Published in Print: 2020-08-27

©2020 Walter de Gruyter GmbH, Berlin/Boston

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