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Mixed Feelings: Natural Text Generation with Variable, Coexistent Affective Categories

机译:混合感情:自然文本生成变量,共存的情感类别

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Conversational agents, having the goal of natural language generation, must rely on language models which can integrate emotion into their responses. Recent projects outline models which can produce emotional sentences, but unlike human language, they tend to be restricted to one affective category out of a few (e.g. Zhao et al. (2018)). To my knowledge, none allow for the intentional coexistence of multiple emotions on the word or sentence level. Building on prior research which allows for variation in the intensity of a singular emotion (Ghosh et al., 2017), this research proposal outlines an LSTM (Long Short-Term Memory) language model which allows for variation in multiple emotions simultaneously.
机译:具有自然语言生成目标的会话代理必须依赖于可以将情感整合到他们的回复中的语言模型。最近的项目大纲模型可以产生情绪句子,但与人类不同,它们往往被限制在几个中的一个情感类别(例如Zhao等人)。据我所知,没有人允许对词语或句子级别的多种情绪的故意共存。在现有研究中建立允许奇异情绪强度的变化(Ghosh等,2017),这项研究提案概述了LSTM(长期内存)语言模型,它允许同时进行多种情绪的变化。

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