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System and Method of Semi-Supervised Learning for Spoken Language Understanding Using Semantic Role Labeling
System and Method of Semi-Supervised Learning for Spoken Language Understanding Using Semantic Role Labeling
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机译:使用语义角色标记的半监督学习的口语理解系统和方法
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摘要
A system and method are disclosed for providing semi-supervised learning for a spoken language understanding module using semantic role labeling. The method embodiment relates to a method of generating a spoken language understanding module. Steps in the method comprise selecting at least one predicate/argument pair as an intent from a set of the most frequent predicate/argument pairs for a domain, labeling training data using mapping rules associated with the selected at least one predicate/argument pair, training a call-type classification model using the labeled training data, re-labeling the training data using the call-type classification model and iteratively several of the above steps until training set labels converge.
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