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In this paper, we create a virtual character that interacts with human player in a sword-fighting task. The data taken from a human player waving a stick as the 'sword' is mapped into the virtual environment, and the result of the collision detection during the virtual interaction is used as a reward for the reinforcement learning. We train a Q-network that animates the virtual character by rotating...
Vehicular ad-hoc networks (VANETs) is a promising approach to the dissemination of spatio-temporal information such as the current traffic condition of a road segment or the availability of a parking space. Due to the constraint of the communication bandwidth, only a limited number of information items may be transmitted upon a vehicle-to-vehicle communication opportunity. Ranking becomes critical...
In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine...
Although researchers have made great progresses on music genre classification in recent years, the need for more accurate system is still not satisfied. In this paper, we propose a method for further reducing the classification error rate based on multiple classifier fusion. First of all, MFCCs and four features from MPEG-7 audio descriptor are extracted in every short time frame, and then a group...
Monaural speech separation is one of the most difficult problems in speech signal processing. In this paper, a new method based on machine learning and computational auditory scene analysis (CASA) is suggested to separate the monaural speech of two-talker. The technique of machine learning is used to learn the grouping cues on isolated clean data from single speaker. By using a factorial-max vector...
We present a statistical machine translation system which uses hierarchical chunking phrases (HCPB). The system can be seen as combination with fundamental ideas from both syntax-based translation and phrase-based translation, because the model not only complies with formal synchronous context-free grammar but also learned partial parsing knowledge CRF (conditional random fields) method. The decoder...
In recent years, some nonlinear dimension reduction methods, named manifold learning, have been proposed and widely used in data visualization and pattern recognition. Of them, Isomap is a representative, which can project data from high-dimensional space into low-dimensional space with local structure preserved perfectly. However, Isomap suffers from the topological stability and is sensitive to...
Several novel methods for nonlinear dimensionality reduction, named as manifold learning, have been proposed recently and widely used in pattern recognition and machine learning. In this paper, we present three face recognition methods based on kernel Isomap, which is a representative manifold learning method using kernel trick. Considering the class label by adjusting the Euclidean distance using...
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