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Computer-based Interlocutor Understanding Using Classifying Conversation Segments
Computer-based Interlocutor Understanding Using Classifying Conversation Segments
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机译:基于计算机的对话者了解使用对话段分类
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摘要
Computer-based natural language understanding of input and output for a computer interlocutor is improved using a method of classifying conversation segments from transcribed conversations. The improvement includes one or more methods of splitting transcribed conversations into groups related to a conversation ontology using metadata; identifying dominant paths of conversational behavior by counting the frequency of occurrences of the behavior for a given path; creating a conversation model comprising conversation behaviors, metadata, and dominant paths; and using the conversation model to assign a probability score for a matched input to the computer interlocutor or a generated output from the computer interlocutor.
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