Audio-based cough counting using independent subspace analysis
Audio and Speech Processing
2021-04-15 v1 Sound
Abstract
In this paper, an algorithm designed to detect characteristic cough events in audio recordings is presented, significantly reducing the time required for manual counting. Using time-frequency representations and independent subspace analysis (ISA), sound events that exhibit characteristics of coughs are automatically detected, producing a summary of the events detected. Using a dataset created from publicly available audio recordings, this algorithm has been tested on a variety of synthesized audio scenarios representative of those likely to be encountered by subjects undergoing an ambulatory cough recording, achieving a true positive rate of 76% with an average of 2.85 false positives per minute.
Keywords
Cite
@article{arxiv.2104.06798,
title = {Audio-based cough counting using independent subspace analysis},
author = {Paul Leamy and Ted Burke and Dan Barry and David Dorran},
journal= {arXiv preprint arXiv:2104.06798},
year = {2021}
}