Abstract
Most work on neural natural language generation (NNLG) focus on controlling the content of the generated text. We experiment with controling several stylistic aspects of the generated text, in addition to its content. The method is based on conditioned RNN language model, where the desired content as well as the stylistic parameters serve as conditioning contexts. We demonstrate the approach on the movie reviews domain and show that it is successful in generating coherent sentences corresponding to the required linguistic style and content.- Anthology ID:
- W17-4912
- Volume:
- Proceedings of the Workshop on Stylistic Variation
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Julian Brooke, Thamar Solorio, Moshe Koppel
- Venue:
- Style-Var
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 94–104
- Language:
- URL:
- https://aclanthology.org/W17-4912
- DOI:
- 10.18653/v1/W17-4912
- Cite (ACL):
- Jessica Ficler and Yoav Goldberg. 2017. Controlling Linguistic Style Aspects in Neural Language Generation. In Proceedings of the Workshop on Stylistic Variation, pages 94–104, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Controlling Linguistic Style Aspects in Neural Language Generation (Ficler & Goldberg, Style-Var 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W17-4912.pdf