Asthmatic versus healthy child classification based on cough and vocalised /a:/ sounds
Title | Asthmatic versus healthy child classification based on cough and vocalised /a:/ sounds |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | BT B, Hee H.I., Teoh O.H., Lee K.P., Kapoor S., Herremans D., Chen J.M. |
Journal | The Journal of the Acoustical Society of America (JASA) |
Volume | 148, EL253 |
Date Published | 09/2020 |
Type of Article | Jasa Express Letters |
Abstract | Cough is a common symptom presenting in asthmatic children. In this investigation, an audio-based classification model is presented that can differentiate between healthy and asthmatic children, based on the combination of cough and vocalised /ɑ:/ sounds. A Gaussian mixture model using mel-frequency cepstral coefficients and constant-Q cepstral coefficients was trained. When comparing the predicted labels with the clinician's diagnosis, this cough sound model reaches an overall accuracy of 95.3%. The vocalised /ɑ:/ model reaches an accuracy of 72.2%, which is still significant because the dataset contains only 333 /ɑ:/ sounds versus 2029 cough sounds. |
URL | https://asa.scitation.org/doi/10.1121/10.0001933 |
DOI | 10.1121/10.0001933 |