Prediction of Personal Characteristics and Emotional State based on Voice Signals using Machine Learning Techniques

Marta Babel Guerreiro, Cátia Cepeda, Joana Sousa, Carolina Maio, João Ferreira, Hugo Gamboa

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

Abstract

Voice signals are a rich source of personal information, leading to the main objective of the present work: study the possibility of predicting gender, age, and emotional valence through short voice interactions with a mobile device (a smartphone or remote control), using machine learning algorithms. For that, data acquisition was carried out to create a Portuguese dataset (consisting in 156 samples). Testing Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF) classifiers and using features extracted from the audio, the gender recognition model achieved an accuracy of 87.8%, the age group recognition model achieved an accuracy of 67.6%, and an accuracy of 94.6% was reached for the emotion model. The SVM algorithm produced the best results for all models. The results show that it is possible to predict not only someone’s specific personal characteristics but also its emotional state from voice signals. Future work should be done in order to improve these mo dels by increasing the dataset
Original languageEnglish
Title of host publicationProceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies
Subtitle of host publicationVolume 4
Pages142-149
Number of pages8
DOIs
Publication statusPublished - 2022
Event15th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS) held as part of 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) - Online
Duration: 9 Feb 202211 Feb 2022

Publication series

NameBiomedical Engineering Systems and Technologies
PublisherSciTePress
ISSN (Print)2184-4305

Conference

Conference15th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS) held as part of 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC)
CityOnline
Period9/02/2211/02/22

Keywords

  • Gender
  • Age
  • Emotion
  • Machine Learning
  • Voice Signal

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