Condition monitoring and fault diagnosis in modern manufacturing automation is of great practical significance. It improves quality and productivity, and prevents damage to machine...
Acquiring, representing and modeling human skills is one of the key research areas in teleoperation, programming-by-demonstration and human-machine collaborative settings. The pro...
ct 7 Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. 8 One most popular technique is minimum classiï...
We present a new statistical model for characterizing texture images based on wavelet-domain hidden Markov models. With a small number of parameters, the new model captures both th...
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, ...
Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive stat...
Ingmar Visser, Maartje E. J. Raijmakers, Peter C. ...
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
This paper presents a new approach to speech synthesis in which a set of cross-word decision-tree state-clustered context-dependent hidden Markov models are used to define a set o...
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
This paper describes an active-camera real-time system for tracking, shape description, and classi"cation of the human face and mouth expressions using only a PC or equivalen...