Over the past decades, a particular focus is given to research on machine learning
techniques for speech processing applications. However, in the past few years, research …

Over the past decade or so, several advances have been made to the design of modern
large vocabulary continuous speech recognition (LVCSR) systems to the point where their …

The Application of Hidden Markov Models in Speech Recognition Page 1 The Application of
Hidden Markov Models in Speech Recognition Full text available at: http://dx.doi.org/10.1561/2000000004 …

Text-to-Speech Synthesis provides a complete, end-to-end account of the process of
generating speech by computer. Giving an in-depth explanation of all aspects of current …

A significant cost in obtaining acoustic training data is the generation of accurate
transcriptions. When no transcription is available, unsupervised training techniques must be …

Almost all present-day continuous speech recognition (CSR) systems are based on hidden
Markov models (HMMs). Although the fundamentals of HMM-based CSR have been …

There is a vast body of literature on LVCSR research and some limitation is necessary in the
scope of this article. We will focus primarily on the techniques that have been successful in …

A deep neural network (DNN) based classifier achieved 27.38% frame error rate (FER) and
15.62% segment error rate (SER) in recognizing five tonal categories in Mandarin Chinese …

A deep neural network (DNN) classifier based only on 40 mel-frequency cepstral coefficients
(MFCCs) achieved 29.99% frame error rate (FER) and 16.86% segment error rate (SER) in …

Language models (LMs) are often constructed by building multiple individual component
models that are combined using context independent interpolation weights. By tuning these …