The Intelligent Real-Time Imaging and Sensing (IRIS) Group, The School of Information Technology and Electrical Engineering, The University of Queensland, Australia QLD 4072, Australia ...

Hidden Markov models (HMMs) have been used as probabilistic models for important tasks such as speech recognition, natural language processing, and process mining. A hidden Markov process is a ...

Hidden Markov Models, or HMMs, are a powerful tool for modeling sequential data, such as speech signals. They can capture the probabilistic dependencies between the observed features and the ...

Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a ...

The popularity of smartphone enables the capability of sensing the human activity, which can be used to provide various intelligent context-aware services. Most existing methods on human motion mode ...

This system implements a Hidden Markov Model (HMM) based approach for digit recognition. The core component is the Viterbi algorithm, which determines the most likely sequence of hidden states (digits ...

Z. Bhahramani, “An Introduction to Hidden Markov Models and Bayesian Networks,” International Journal of Pattern Recognition and Artificial Intelligence, Vol. 15, No. 1, 2001, pp. 9-42.

Then, it uses the classifier it has learned to detect the text in test-image- file.png, using (1) simple Bayes net (2) Hidden Markov Model with variable elimination, and (3) Hidden Markov Model with ...

To this end, we introduce the Hidden-Articulator Markov Model (HAMM), a model which directly integrates articulatory information into speech recognition. The HAMM is an extension of the ...