In this paper we consider a feature estimation approach for vocal fold pathology classification, based on digital signal processing theory. This problem is addressed by formulating a stochastic maximum likelihood (ML) estimation procedure, based on Estimation-Maximization (EM) algorithm. New spectral parameters of speech, noted as Spectral Pathology Component (SPC) is estimated. For classificat...

There are different algorithms for vocal fold pathology diagnosis. These algorithms usually have three stages which are Feature Extraction, Feature Reduction and Classification. While the third stage implies a choice of a variety of machine learning methods, the first and second stages play a critical role in performance and accuracy of the classification system. In this paper we present initia...

Pathology is the study and diagnosis of disease. Due to the nature of job, unhealthy habits and voice abuse, the people are subjected to the risk of voice problems. The diagnosis of vocal and voice disorders should be in the early stage otherwise it causes changes in the normal signal. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. Therefore, th...

Acoustic analysis of voice features can complete the invasive observation-based methods for the diagnosis of vocal fold pathologies. Selection of an appropriate feature extraction method from the voice can significantly improve the diagnostic results for patients with vocal disorders. In this paper, the performance of nonlinear dynamics and acoustical perturbation features is evaluated in order...