With the improvement in processing systems, machine learning applications are finding widespread use in almost all sectors of technology. Image recognition is one application of machine learning which has become widely ...

Speech processing systems are widely used in existing commercial applications, including virtual assistants in smartphones and home assistant devices. Speech-based commands provide convenient hands-free functionality for ...

This thesis investigates the Federation of Medical Machine Learning Models. Medical data is by its very nature sensitive - which makes the free sharing of medical information difficult. This data often contains very useful ...

Speaker diarization is an unsupervised task that determines "who spoke and when" within input audio stream. It consists of four sub-systems: (i) speech activity detection (SAD); (ii) speaker segmentation and modeling; ...

In many pattern recognition or machine learning applications, deep learning models or deep neural networks have provided superior performance relative to feature-based classifiers. Although there exist a number of publicly ...

Graphics processing units (GPUs) are being widely used as co-processors in many domains to accelerate general-purpose workloads that are data-parallel and computationally intensive, i.e., GPGPU. An emerging usage domain ...

Chronic Respiratory diseases, mainly asthma and Chronic Obstructive Pulmonary Disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) ...

Evaluation of capacity fade in Li-ion batteries in the ballparks of energy research has assumed significant importance in recent times extensively owing to growing demand and need for portable power supplies and electric ...

Speech emotion recognition solutions designed under controlled conditions do not translate well into real-life applications. The first step to address this issue is developing a large, natural emotional database. Current ...

Despite significant efforts over the last few years to build a robust automatic speech recognition (ASR) systems for different acoustic settings, the performance of the current state-of-the-art technologies significantly ...