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This paper proposes a novel distributed training method of Conditional Random Fields (CRFs) by utilizing the clusters built from commodity computers. The method employs Message Passing Interface (MPI) to deal with large-scale data in two steps. Firstly, the entire training data is divided into several small pieces, each of which can be handled by one node. Secondly, instead of adopting a root node...
This paper proposes a novel method of Chinese word segmentation utilizing morphology information. The method introduces morphology into statistical model to capture structural relationship within word. It improves the conventional Conditional Random Fields (CRFs) models on the ability of representing the structure information. Firstly, a word-segmented Chinese corpus is annotated with morphology tags...
This paper reports our work on Chinese semantic role labeling, which takes advantage of hierarchical semantic knowledge from a common sense knowledge base named HowNet. On one hand, the words in lexical features such as predicate and head word are generalized with their hypernyms in HowNet. On the other hand, the hypernym-hyponym relation between sememes is used to capture the semantic similarity...
A novel method is proposed, which is for performing just-in- time adaptation on language models in Chinese speech recognition using Web search engines. Latent semantic analysis (LSA) is employed to change the probability distribution of N-gram language model. The method has two advantages. First, it needs relatively small amount of data which can be obtained from Web on-the-fly. Second, comparing...
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