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Modern French Poetry Generation with RoBERTa and GPT-2

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Abstract

We present a novel neural model for modern poetry generation in French. The model consists of two pretrained neural models that are fine-tuned for the poem generation task. The encoder of the model is a RoBERTa based one while the decoder is based on GPT-2. This way the model can benefit from the superior natural language understanding performance of RoBERTa and the good natural language generation performance of GPT-2. Our evaluation shows that the model can create French poetry successfully. On a 5 point scale, the lowest score of 3.57 was given by human judges to typicality and emotionality of the output poetry while the best score of 3.79 was given to understandability.
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Dates and versions

hal-03746349 , version 1 (05-08-2022)

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  • HAL Id : hal-03746349 , version 1

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Mika Hämäläinen, Khalid Alnajjar, Thierry Poibeau. Modern French Poetry Generation with RoBERTa and GPT-2. 13th International Conference on Computational Creativity (ICCC) 2022, ICCC, Jun 2022, Bolzano, Italy. ⟨hal-03746349⟩
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