In this invited paper, my overview material on the same topic as presented in the plenary
overview session of APSIPA-2011 and the tutorial material presented in the same …

Automatic Speech Recognition (ASR) has historically been a driving force behind many
machine learning (ML) techniques, including the ubiquitously used hidden Markov model …

This monograph provides an overview of general deep learning methodology and its
applications to a variety of signal and information processing tasks. The application areas …

A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …

While neural, encoder-decoder models have had significant empirical success in text
generation, there remain several unaddressed problems with this style of generation …

Modelling sequential data is important in many areas of science and engineering. Hidden
Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

As an extension to the popular hidden Markov model (HMM), a hidden semi-Markov model
(HSMM) allows the underlying stochastic process to be a semi-Markov chain. Each state has …

This paper presents a brief survey on Automatic Speech Recognition and discusses the
major themes and advances made in the past 60 years of research, so as to provide a …

Abstract Automatic Speech Recognition (ASR) systems can be trained to achieve
remarkable performance given large amounts of manually transcribed speech, but large …