In this correspondence, on-line quasi-Bayes adaptation of the mixture coefficients and mean vectors in semicontinuous hidden Markov model (SCHMM) is studied. The viability of the proposed algorithm is confirmed and the related practical issues are addressed in a specific application of on-line speaker adaptation using a 26-word English alphabet vocabulary.

We approach the singing phrase audio to score matching problem by using phonetic and duration information – with a focus on studying the jingju a cappella singing case. We argue that, due to the existence of a basic melodic contour for each mode in jingju music, only using melodic information (such as pitch contour) will result in an ambiguous matching. This leads us to propose a matching appro...

Search tasks in users’ query sequences are dynamic and interconnected. The formulation of search tasks can be influenced by multiple latent factors such as user characteristics, product features and search interactions, which makes search task identification a challenging problem. In this paper, we propose an unsupervised approach to identify search tasks via topic membership along with topic t...

Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms (earthquakes) are often hard to detect and classify. Here, we propose to use models from speech synthesis which extend the double stochastic models f...

In the classical hidden Markov chain (HMC) model we have a hidden chain X , which is a Markov one and an observed chain Y . HMC are widely used; however, in some situations they have to be replaced by the more general “hidden semi-Markov chains” (HSMC), which are particular “triplet Markov chains” (TMC) ) , , ( Y U X T = , where the auxiliary chain U models the semi-Markovianity of X . Otherwis...

in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...

This paper presents a technique for estimating the degree or intensity of emotional expressions and speaking styles appeared in speech. The key idea is based on a style control technique for speech synthesis using multiple regression hidden semi-Markov model (MRHSMM), and the proposed technique can be viewed as the inverse process of the style control. We derive an algorithm for estimating pred...

The conformational kinetics of enzymes can be reliably revealed when they are governed by Markovian dynamics. Hidden Markov Models (HMMs) are appropriate especially in the case of conformational states that are hardly distinguishable. However, the evolution of the conformational states of proteins mostly shows non-Markovian behavior, recognizable by non-monoexponential state dwell time histogra...

There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM. However, in many settings the HDP-HMM’s strict Markovian constraints are undesirable, particularly if we wish to learn or encode non-geometric state durations. We can extend the HDP-HMM to capture such structure by drawing upon explicit...

In HMM-based speech synthesis, it is important to correctly model duration because it has a significant effect on the perceptual quality of speech, such as rhythm. For this reason, hidden semi-Markov model (HSMM) is commonly used to explicitly model duration instead of using the implicit state duration model of HMM through its transition probabilities. The cost of using HSMM to improve duration...