Current HMM-based low bit rate speech coding systems work with phonetic vocoders. Pitch contour coding (on frame or phoneme level) is usually fairly orthogonal to other speech coding parameters. We make an assumption in our work that the speech signal contains supra-segmental cues. Hence, we present encoding of the pitch on the syllable level, used in the framework of a recognition/synthesis sp...

In HMM-based TTS, while the segmental quality of synthesized speech is quite acceptable, intonation, especially at the sentence level, tends to be somewhat bland. The maximum likelihood (ML) criterion used in HMM training and parameter trajectory generation is partially responsible for the blandness. Additionally, the F0 trajectory thus generated has a smaller dynamic range than that of natural...

Prediction of physical particular phenomenon is based on knowledges of the phenomenon. Theses knowledges help us to conceptualize this phenomenon throw different models. Hidden Markov Models (HMM) can be used for modeling complex processes. We use this kind of models as tool for fault diagnosis systems. Nowadays, industrial robots living in stochastic environment need faults detection to preven...

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...

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...

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...

According to the wide application of segmental lining in mechanized tunneling, recognizing the behavior of segmental lining joints is important in tunnels designing. In the structural analysis of the tunnel segmental lining, segmental joints can be considered as elastic joints, and their stiffness characteristics are affected by the rotational, shear, and axial stiffness. The purpose of this wo...