GPoeT: a Language Model Trained for Rhyme Generation on Synthetic Data
Andrei Popescu-Belis,
Àlex R. Atrio,
Bastien Bernath
et al.
Abstract:Poem generation with language models requires the modeling of rhyming patterns. We propose a novel solution for learning to rhyme, based on synthetic data generated with a rulebased rhyming algorithm. The algorithm and an evaluation metric use a phonetic dictionary and the definitions of perfect and assonant rhymes. We fine-tune a GPT-2 English model with 124M parameters on 142 MB of natural poems and find that this model generates consecutive rhymes infrequently (11%). We then fine-tune the model on 6 MB of s… Show more
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