NAACL 2022: Zero-shot Sonnet Generation with Discourse-level Planning and Aesthetics Features https://aclanthology.org/2022.naacl-main.262/
- Step 1 - Keyword generation
- Step 2 - Rhyme word generation
- Step 3 - Add simile and imagery
- Step 4 - Decoding
A few notes:
- Both step 1&2 are located in the keyword folder.
- To directly use the pretrained model, run inference_bart_keywords_gen.ipynb and load the model from https://huggingface.co/FigoMe/sonnet_keyword_gen. Then at decoding time, load the pretrained model from https://huggingface.co/FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse
- To train the keyword model yourself, run train-keywords-bart.ipynb (we shifted from T5 to bart)
Please cite our paper if they are helpful to your work !
@inproceedings{tian-peng-2022-zero,
title = "Zero-shot Sonnet Generation with Discourse-level Planning and Aesthetics Features",
author = "Tian, Yufei and Peng, Nanyun",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
year = "2022",
address = "Seattle, United States"
}