Yu-Yu Chou

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In this paper, we propose a semantic query expansion approach by extending the query-regularized mixture model to include latent topics and apply it to spoken documents. We also propose to use context feature vectors for spoken segments to train SVM models to enhance the posterior-weighted normalized term frequencies in lattices. Experiments on Mandarin(More)
This paper addresses the classification problem for applications with extensive amounts of data and complex features. The learning system developed utilizes a hierarchical multiple classifier scheme and is flexible, efficient, highly accurate and of low cost. The system has several novel features: 1) It uses a graph-theoretic clustering algorithm to group(More)
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