The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical for learning from sequential and time-series data. A sticky HDP-HMM proposed to strengthen self-persistence probability in HDP-HMM. However, entangles strength prior transition together, limiting its expressiveness. Here, we propose more general mo...

This paper describes an improved algorithm, motivated by fuzzy logic theory, for the selection of speech segments for concatenative synthesis from a huge database. Triphone HMM clustering is employed as an adaptive measure for articulatory similarity within a given database. Stress level contours are evaluated in the context of their surrounding vocalic peaks. The algorithm uses a beam search t...

Abstract This work attempts to approximate a linear Gaussian system with finite-state hidden Markov model (HMM), which is found useful in dealing challenges designing networked control systems An indirect approach developed, where state-space (SSM) firstly identified for and the SSM then used as an emulator learning HMM. In proposed method, training data HMM are obtained from generated by throu...

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...

Handover during mobile communications is becoming the general task in heterogeneous wireless networks. To make handover efficient and faster without leaking data with less delay is prime objective. Since from last two decades, many on-going research studies presented to achieve these goals. Still many research works going on to claim more robust performance. In this paper presenting new method ...

The paper presents Bangla word speech recognition using two novel approaches with a comprehensive analysis. The first approach is based on spectral analysis and fuzzy logic and the second one uses Mel-Frequency Cepstral Coefficients (MFCC) analysis and feed-forward back-propagation neural networks. As human speech is imprecise and ambiguous, fuzzy logic – the base of which is indeed linguistic ...

The hidden Markov model (HMM), used with Gaussian Process (GP) as an emission model, has been widely to sequential data in complex form. This study introduces the hybrid Bayesian HMM GP using SM kernel (HMM-GPSM) estimate state of each time-series observation, that is, sequentially observed from a single channel. We then propose scalable inference method train HMM-GPSM large-scale sequences dat...