A common task in many applications is to find persons who are knowledgeable about a given topic (i.e., expert finding). In this paper, we propose and develop a general probabilistic framework for studying expert finding problem and derive two families of generative models (candidate generation models and topic generation models) from the framework. These models subsume most existing language mo...

Experimental and numerical techniques to characterize the response of premixed methane-air flames to acoustic waves are discussed and applied to a multi-slit Bunsen burner. The steady flame shape, flame front kinematics and flow field of acoustically exited flames, as well as the flame transfer function and matrix are computed. The numerical results are compared with experiments. The influence ...

The goal of personalized history-based recommendation is to automatically output a distribution over all the items given a sequence of previous purchases of a user. In this work, we present a novel approach that uses a recurrent network for summarizing the history of purchases, continuous vectors representing items for scalability, and a novel attention-based recurrent mixture density network, ...

In this paper, we present our recent studies of F0 estimation from the surface electromyographic (EMG) data using a Gaussian mixture model (GMM)-based voice conversion (VC) technique, referred to as EMG-to-F0. In our approach, a support vector machine recognizes individual frames as unvoiced and voiced (U/V), and voiced F0 contours are discriminated by the trained GMMbased on the manner of mini...

This study presents a Child Video Dataset (CVDS) that has numerous videos of different ages and situation of children. To simulate a babysitter’s vision, our application was developed to track objects in a scene with the main goal of creating a reliable and operative moving child-object detection system. The aim of this study is to explore novel algorithms to track a child-object in an indoor a...

Detecting shadows is needed for object detection methods because shadows often have a harmful effect on the result. Shadow detection methods based on shadow models are proposed. The shadow model should be updated to detect shadows which are not included in the learning data. In this paper, a new method for updating the shadow model for shadow detection is proposed. The proposed method models sh...

This paper presents methods to improve speech recognition accuracy by incorporating automatic lip reading. The paper improves lip reading accu­ racy by following approaches; 1)collection of im­ age and speech synchronous data of 5240 words， 2)feature extraction of 2・dimensional power spect日 around a mouth and 3)sub-word unit HMMs with tied-mixture distribution(Tied-Mixture HMMs). Ex­ periments ...

Nitrous oxide (N2O) is a potent greenhouse gas (GHG) emitted from agricultural soils and influenced by nitrogen (N) fertiliser management weather soil conditions. Source partitioning N2O emissions related to practices conditions could suggest effective mitigation strategies. Multispecies swards can maintain herbage yields at reduced N rates compared grass monocultures may reduce losses the wide...

Mixture models have been widely used in cluster analysis. Traditional mixture densities-based clustering algorithms usually predefine the number of clusters via random selection or contend based knowledge. An improper pre-selection of the number of clusters may easily lead to bad clustering outcome. Expectation-maximization (EM) algorithm is a common approach to estimate the parameters of mixtu...

In this work we propose an approach for generalization in continuous domain Reinforcement Learning that, instead of using a single function approximator, tries many different function approximators in parallel, each one defined in a different region of the domain. Associated with each approximator is a relevance function that locally quantifies the quality of its approximation, so that, at each...