4 accepted papers
Breathing is essential to human survival, which carries information about a person’s physiological and psychological state. Mostly breath sound boundaries are marked manually before being used for any task such as classification, spectral analysis, etc., which is very tedious. Various techniques hav…
Dysarthria due to Amyotrophic Lateral Sclerosis (ALS) and Parkinson’s disease (PD) impacts both articulation and prosody in an individual’s speech. Complex deep neural networks exploit these cues for detection of ALS and PD. These are typically done using recordings in laboratory condition. This stu…
Non-speech sounds (cough, wheeze) are typically known to perform better than speech sounds for asthmatic and healthy subject classification. In this work, we use sustained phonations of speech sounds, namely, /α:/, /i:/, /u:/, /eI/, /ou/, /s/, and /z/ from 47 asthmatic and 48 healthy controls. We co…
In this paper, we consider 2-class and 3-class classification problems for classifying patients with Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD), and Healthy Controls (HC) using a CNNLSTM network. Classification performance is examined for three different tasks, namely, Spontaneous…