semi Markov models (HSMMs) are typically used in statistical parametric speech synthesis to represent probability densities of acoustic features given contextual factors. This paper addresses three major limitations of this decision tree-based structure: i) the decision tree structure lacks adequate context generalization; ii) it is unable to express complex context dependencies; iii) parameter...

the air transport industry is seeking to manage risks in air travels. its main objective is to detect abnormal behaviors in various flight conditions. the current methods have some limitations and are based on studying the risks and measuring the effective parameters. these parameters do not remove the dependency of a flight process on the time and human decisions. in this paper, we used an hmm...

In applications of Bayesian analysis one problem that arises is the evaluation of the sensitivity, or robustness, of the adopted inferential procedure with respect to the components of the formulated statistical model. In particular, it is of interest to study robustness with respect to the prior, when this latter cannot be uniquely elicitated, but a whole class Γ of probability measures, agree...

Current speech recognition systems are often based on HMMs with state-clustered Gaussian Mixture Models (GMMs) to represent the context dependent output distributions. Though highly successful, the standard form of model does not exploit any relationships between the states, they each have separate model parameters. This paper describes a general class of model where the context-dependent state...

We propose a new machine-learning framework called the Hierarchical Sequential Memory for Music, or HSMM. The HSMM is an adaptation of the Hierarchical Temporal Memory (HTM) framework, designed to make it better suited to musical applications. The HSMM is an online learner, capable of recognition, generation, continuation, and completion of musical structures.

The primary objective of engineering asset management is to optimize assets service delivery potential and to minimize the related risks and costs over their entire life through the development and application of asset health and usage management in which the health and reliability prediction plays an important role. In real-life situations where an engineering asset operates under dynamic oper...

Abdominal auscultation is a convenient, safe and inexpensive method to assess bowel conditions, which essential in neonatal care. It helps early detection of dysfunctions allows timely intervention. This paper presents sound assist the auscultation. Specifically, Convolutional Neural Network (CNN) proposed classify peristalsis non-peristalsis sounds. The classification then optimized using Lapl...

Hidden Markov model (HMM) has been a popular choice for financial time series modeling due to its advantage in capturing dynamic regimes. However, HMM's implicit assumption that the state duration follows geometric distribution is too strong hold practice. In this work, we propose regularized vector autoregressive hidden semi-Markov analyze multivariate series. One challenge such setting number...