Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

The speech signal is like the black box of human beings where much information is hidden.
The treatment of this signal provides us with the speaker's identity. In a way, it is similar to an …

Parkinson's Disease (PD) is a prevalent neurodegenerative disorder with sig-nificant clinical
implications. Early and accurate diagnosis of PD is crucial for timely intervention and …

The early detection of COVID-19 is a challenging task due to its deadly spreading nature
and existing fear in minds of people. Speech-based detection can be one of the safest tools …

Deep brain simulations play an important role to study physiological and neuronal behavior
during Parkinson's disease (PD). Electroencephalogram (EEG) signals may faithfully …

Biomedical engineers prefer decision forests over traditional decision trees to design state-
of-the-art Parkinson's Detection Systems (PDS) on massive acoustic signal data. However …

We adopt Bidirectional Long Short-Term Memory (BiLSTM) neural network and Wavelet
Scattering Transform with Support Vector Machine (WST-SVM) classifier for detecting …

To diagnose Parkinson's disease (PD), it is necessary to monitor the progression of
symptoms. Unfortunately, diagnosis is often confirmed years after the onset of the disease …

Parkinson's disease (PD) is an incurable neurodegenerative disorder which affects over 10
million people worldwide. Early detection and correct evaluation of the disease is critical for …

Among the several ways followed for detecting Parkinson's disease, there is the one based
on the speech signal, which is a symptom of this disease. In this paper focusing on the …