The method which is called the “tandem approach” in speech recognition has been shown to increase performance by using classifier posterior probabilities as observations in a...
In this paper the development of a prototypic mobile voice control for navigating autonomous robots within a multi robot system is described. As basis for the voice control a hidde...
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Abstract--Domain knowledge for web applications is currently being made available as domain ontology with the advent of the semantic web, in which semantics govern relationships am...
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
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 present a technique which complements Hidden Markov Models by incorporating some lexicalized states representing syntactically uncommon words. 'Our approach examines the d...
Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov mod...
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Background: Profile Hidden Markov Models (pHMMs) are a widely used tool for protein family research. Up to now, however, there exists no method to visualize all of their central a...