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Affect LM: A Neural Language Model for Customizable Affective Text Generation

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Figure

Table 1: Summary of corpora used in this paper. CMU-MOSI and SEMAINE are observed to havehigher emotional content than Fisher and DAIC corpora.
Table 2: Example sentences generated by the model conditioned on different affect categories
Figure 2: Amazon Mechanical Turk study results for generated sentences in the target affect categoriespositive emotion, negative emotion, angry, sad, and anxious (a)-(e)
Table 3: Evaluation perplexity scores obtained bythe baseline and Affect-LM models when trainedon Fisher and subsequently adapted on DAIC,SEMAINE and CMU-MOSI corpora

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