One of the main clinical applications of speech technology is in voice-enabled assistive technology for people with disordered speech. Progress in this area is hampered by a sparseness in suitable data and recent research have focused on ways of incorporating knowledge about typical (i.e., un-impaired) speech through the use of e.g., deep belief neural networks. This paper presents a new way of...

Image location prediction is to estimate the geolocation where an image is taken. Social image contains heterogeneous contents, which makes image location prediction nontrivial. Moreover, it is observed that image content patterns and location preferences correlate hierarchically. Traditional image location prediction methods mainly adopt a single-level architecture, which is not directly adapt...

Previous algorithms for the construction of Bayesian belief network structures from data have been either highly dependent on con­ ditional independence (CI) tests, or have re­ quired an ordering on the nodes to be sup­ plied by the user. We present an algorithm that integrates these two approaches CI tests are used to generate an ordering on the nodes from the database which is then used to re...

Bayesian Network has provided a convenient frame structure to express causal relationship, by regarding influence diagram as a special Bayesian Network, then the value of each decision variable is imposed externally to meet the goals, rather than derive from determination probability of father node. Using influence diagram to describe the node types of directed acyclic graph has been studied, w...

In this report we present an extension to Continuous Time Bayesian Networks (CTBN) called Generalized Continuous Time Bayesian Networks (GCTBN). The formalism allows one to model, in addition to continuous time delayed variables (with exponentially distributed transition rates), also non delayed or “immediate” variables, which act as standard chance nodes in a Bayesian Network. This allows the ...

Previous algorithms for the recovery of Bayesian belief network structures from data have been either highly dependent on conditional independence (CI) tests, or have required an ordering on the nodes to be supplied by the user. We present an algorithm that integrates these two approaches-CI tests are used to generate an ordering on the nodes from the database which is then used to recover the ...