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.
翻译:我们用法语为现代诗歌一代展示了新型神经模型。该模型由两种经过训练的神经模型组成,这些模型经过微调,以完成诗歌创作任务。模型的编码是罗贝塔(RoBERTA)的编码,而解码器则以GPT-2为基础。这样,该模型可以受益于罗贝塔(RoBERTA)的优秀自然语言理解性能和GPT-2(GPT-2)的优良自然语言生成性能。我们的评估表明,该模型可以成功地创造出法国诗歌。在5点尺度上,人类法官对产出诗的典型性和情绪性给予3.57分最低分,而3.79分的最佳分则用于理解性。