Machine learning based animal emotion classification using audio signals
Sound
2025-03-25 v1 Machine Learning
Abstract
This paper presents the machine learning approach to the automated classification of a dog's emotional state based on the processing and recognition of audio signals. It offers helpful information for improving human-machine interfaces and developing more precise tools for classifying emotions from acoustic data. The presented model demonstrates an overall accuracy value above 70% for audio signals recorded for one dog.
Cite
@article{arxiv.2503.18138,
title = {Machine learning based animal emotion classification using audio signals},
author = {Mariia Slobodian and Mykola Kozlenko},
journal= {arXiv preprint arXiv:2503.18138},
year = {2025}
}
Comments
5 pages, 3 figures. This paper was originally published in 2022 International Conference on Innovative Solutions in Software Engineering (ICISSE), available: https://zenodo.org/records/7514136