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MODELING MULTIPARTY CONVERSATION DYNAMICS: SPEAKER, RESPONSE, ADDRESSEE SELECTION USING A NOVEL DEEP LEARNING APPROACH
MODELING MULTIPARTY CONVERSATION DYNAMICS: SPEAKER, RESPONSE, ADDRESSEE SELECTION USING A NOVEL DEEP LEARNING APPROACH
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机译:多方对话动力学建模:说话者,响应,使用新型深度学习方法的收件人选择
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摘要
An information processing system, a computer program product, and methods for modeling multi-party dialog interactions. A method includes learning, directly from data obtained from a multi-party conversational channel, to identify particular multi-party dialog threads as well as participants in one or more conversations. Each participant utterance being converted to a continuous vector representation updated in a model of the multi-party dialog relative to each participant utterance and according to each participant's role selected from the set of: sender, addressee, or observer. The method trains the model to choose a correct addressee and a correct response for each participant utterance, using a joint selection criterion. The method learns directly from the data obtained from the multi-party conversational channel, which dialog turns belong to each particular multi-party dialog thread.
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