Unsegmented Heart Sound Classification Using Hybrid CNN-LSTM Neural Networks.

Cardiac Auscultation, an integral part of the physical examination of a patient, is essential for early diagnosis of cardiovascular diseases (CVDs). The ability to accurately diagnose the heart sounds requires experience and expertise, which is lacking in doctors in the early years of clinical practice. Thus, there is a need for an automatic diagnostic tool that would aid medical practitioners with their diagnosis.

Noise Robust Detection of Fundamental Heart Sound using Parametric Mixture Gaussian and Dynamic Programming.

In this work, we propose an unsupervised algorithm for fundamental heart sound detection. We propose to detect the heart sound candidates using the stationary wavelet transforms and group delay. We further propose an objective function to select the candidates.

Two step convolutional neural network for automatic glottis localization and segmentation in stroboscopic videos.

Precise analysis of the vocal fold vibratory pattern in a stroboscopic video plays a key role in the evaluation of voice disorders. Automatic glottis segmentation is one of the preliminary steps in such analysis. In this work, it is divided into two subproblems namely, glottis localization and glottis segmentation.

Effect of source filter interaction on isolated vowel-consonant-vowel perception.

Source-filter interaction explains the drop in pitch in voiced consonant due to constriction in the vocal tract during vowel-consonant-vowel (VCV) production. In this work, a perceptual study is conducted where the pitch contour in the voiced consonant region is modified to four different levels and a listening test is performed to assess the naturalness of the VCVs synthesized with the modified pitch contour. The listening test with 30 listeners shows no statistically significant difference between the naturalness of the original and synthesized VCVs with modified pitch indicating that pitch drop due to source-filter interaction may not be critical for the perceived naturalness of VCVs.