Yi-Chung Lin

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In the past researches, several kinds of information have been explored to assess the confidence measure or to select the confidence tag for a word/phrase. However, the contextual confidence information is little touched. In this paper, we propose a concept-based probabilistic verification model to integrate the contextual confidence information. In this(More)
To compare the in vitro antibacterial efficacies and resistance profiles of rifampin-based combinations against methicillin-resistant Staphylococcus aureus (MRSA) in a biofilm model, the antibacterial activities of vancomycin, teicoplanin, daptomycin, minocycline, linezolid, fusidic acid, fosfomycin, and tigecycline alone or in combination with rifampin(More)
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of insufficient training data and approximation error introduced by the language model, traditional statistical approaches, which resolve ambiguities by indirectly and implicitly using(More)
Statistical approaches to natural language processing generally obtain the parameters by using the maximum likelihood estimation (MLE ) method. The MLE approaches, however, may fail to achieve good performance in difficult tasks, because the discrimination and robustness issues are not taken into consideration in the estimation processes. Motivated by that(More)
In some dialogue systems, the design of dialogue strategy is bound tightly to the domain by straightforwardly hard-coding the response actions into the system. Such a paradigm is quite easy to build up a prototype system, but makes it difficult to port the system across different domains. This paper presents a domain-transparent design of dialogue(More)
Statistical NLP models usually only consider coarse information and very restricted context to make the estimation of parameters feasible. To reduce the modeling error introduced by a simplified probabilistic model, the Classitication and Regression Tree (CART) method was adopted in this paper to select more discriminative features for automatic model(More)
In spoken dialogue systems, sentence verification technique is very useful to avoid misunderstanding user’s intention by rejecting out-of-domain or bad quality utterances. However, compared with word verification and concept verification, sentence verification has been seldom touched in the past. In this paper, we propose a sentence verification approach(More)