Learning Hidden Markov Models for Regression using Path Aggregation

Introducing Busy Customer Portfolio Using Hidden Markov Model

Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Using Input-Output Hidden Markov Models for the Aggregation of Performance Models

This paper describes a new idea how to use InputOutput Hidden Markov Models (IOHMMs) for the aggregation of performance models and reports about corresponding first experiments. The parameters of the IOHMM are calculated from observation sequences obtained from the input/output behaviour of the original model.

Bridging Viterbi and posterior decoding: a generalized risk approach to hidden path inference based on hidden Markov models

Motivated by the unceasing interest in hidden Markov models (HMMs), this paper reexamines hidden path inference in these models, using primarily a risk-based framework. While the most common maximum a posteriori (MAP), or Viterbi, path estimator and the minimum error, or Posterior Decoder (PD) have long been around, other path estimators, or decoders, have been either only hinted at or applied ...