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This paper applies Support Vector Machine (SVM) algorithm to carry on Chinese College English Test Band 4 (CET-4) forecast research, forms the sample set with 2000- 2009 year CET-4 data, establishes SVM model including the influencing factor and CET-4 result. Use SVM on the training and learning for input and output data, approach functional relations which the historical data conceals, complete mapping...
Coreference is a common linguistic phenomenon in natural language understanding, it plays an important role in simplifying the expression and linking up the context. In this paper, the algorithm of support vector machines is applied to solve the problem of Chinese coreference, we consider fully the important characteristics which related to coreference and integrate them effectively to build model...
In this paper, we propose to use various global features for discriminative reranking in an SMT framework. We employ an online large-margin based training algorithm for the structural output support vector machines based on the margin infused relaxed algorithm. Besides the standard features used, such as decoder's scores, source and target sentences, alignments and part-of-speech tags, we include...
This paper proposes a word-by-word model selection approach to domain adaptation for Word Sense Disambiguation. By this approach, the model for a target word is automatically selected from a candidate model set, which is comprised of improved self-training models and a supervised model. The improved self-training uses sense priors to prevent its iteration from converging into undesirable states. Experimental...
This paper describes the system submitted by Loquendo and Politecnico di Torino (LPT) for the 2009 NIST Language Recognition Evaluation. The system is a combination of classifiers based on two core acoustic models and on two core phone tokenizers. It exploits several state-of-the-art techniques that have been successfully applied in recent years both in speaker and in language recognition.
Traditional text chunking approach is to identify many phrases using only one model, and the same features are used to identify these phrases too. So the helpful features of each phrase are ignored. In fact, different phrases have different helpful features. In this paper, the concept of ??sensitive feature?? is proposed, and the sensitive features of eleven English types and seven Chinese types of...
This study investigates the domain adaptation problem for nature language processing tasks in the distributional view. A novel method is proposed for domain adaptation based on the hybrid model which combines the discriminative model with the generative model. The advantage of the discriminative model is to have lower asymptotic error, while the advantage of the generative model can easily incorporate...
Pronunciation-translated person names (PPN) bring ambiguities to Chinese word segmentation. In this paper, we regard PPN recognition as a binary classification problem. We propose a hybrid approach that combines conditional random fields (CRF) model and support vector machines (SVM) model for the task of recognizing PPN. The experiments show that the performance of the hybrid model is better than...
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