Papers by Tushar Goswamy
Adapting a Language Model for Controlled Affective Text Generation (2020.coling-main)
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| Challenge: | Existing models for affective text generation fail to capture emotional aspects of conversations without explicit affective information. |
| Approach: | They propose to incorporate emotion as prior for the probabilistic state-of-the-art text generation model such as GPT-2 and incorporate emotion into the model to ensure grammatical correctness. |
| Outcome: | The proposed model outperforms existing models in all intensities and is robust to human evaluations. |