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)|
|Type of Article||Jasa Express Letters|
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.