首页> 外国专利> 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

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

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.
机译:信息处理系统,计算机程序产品以及用于建模多方对话交互的方法。一种方法包括直接从从多方对话渠道获得的数据中学习,以标识特定的多方对话线程以及一个或多个对话中的参与者。将每个参与者的话语转换为在多方对话模型中相对于每个参与者的话语并根据从以下一组者中选择的每个参与者的角色来更新的连续矢量表示:发送者,收件人或观察者。该方法使用联合选择标准训练模型为每个参与者的话语选择正确的收件人和正确的响应。该方法直接从多方对话通道获得的数据中学习,哪个对话转弯属于每个特定的多方对话线程。

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