This paper provides a brief survey of the basic concepts and algorithms used for Machine
Learning and its applications. We begin with a broader definition of machine learning and …

This paper examines how people communicate with computers using speech. Automatic
speech recognition (ASR) transforms speech into text, while automatic speech synthesis [or …

An important issue in applying SVMs to speech recognition is the ability to classify variable
length sequences. This paper presents extensions to a standard scheme for handling this …

Most large vocabulary continuous speech recognition (LVCSR) systems in the past decade
have used a context-dependent (CD) phone as the fundamental acoustic unit. We present …

Spelling is a useful way of communicating an exact sequence of letters. When people spell a
word to one another, they tend to elaborate on the letters being spelled by using additional …

Interpreting sensor data in Internet-of-Things applications is a challenging problem
particularly in embedded systems. We consider sensor data analytics where machine …

Hidden Markov models (HMM) with Gaussian mixture observation densities are the
dominant approach in speech recognition. These systems typically use a representational …

Accessible rapid COVID-19 testing continues to be necessary and several studies involving
deep neural network (DNN) methods for detection have been published. As part of a …

As the COVID-19 pandemic continues, rapid non-invasive testing has become essential.
Recent studies and benchmarks motivates the use of modern artificial intelligence (AI) tools …

Most contemporary laboratory recognizers require too much memory to run, and are too
slow for mass applications. One major cause of the problem is the large parameter space of …