Contextual Text Style Transfer
Yu Cheng, Zhe Gan, Yizhe Zhang, Oussama Elachqar, Dianqi Li, Jingjing Liu
Abstract
We introduce a new task, Contextual Text Style Transfer - translating a sentence into a desired style with its surrounding context taken into account. This brings two key challenges to existing style transfer approaches: (I) how to preserve the semantic meaning of target sentence and its consistency with surrounding context during transfer; (ii) how to train a robust model with limited labeled data accompanied by context. To realize high-quality style transfer with natural context preservation, we propose a Context-Aware Style Transfer (CAST) model, which uses two separate encoders for each input sentence and its surrounding context. A classifier is further trained to ensure contextual consistency of the generated sentence. To compensate for the lack of parallel data, additional self-reconstruction and back-translation losses are introduced to leverage non-parallel data in a semi-supervised fashion. Two new benchmarks, Enron-Context and Reddit-Context, are introduced for formality and offensiveness style transfer. Experimental results on these datasets demonstrate the effectiveness of the proposed CAST model over state-of-the-art methods across style accuracy, content preservation and contextual consistency metrics.- Anthology ID:
- 2020.findings-emnlp.263
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2915–2924
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.263
- DOI:
- 10.18653/v1/2020.findings-emnlp.263
- Cite (ACL):
- Yu Cheng, Zhe Gan, Yizhe Zhang, Oussama Elachqar, Dianqi Li, and Jingjing Liu. 2020. Contextual Text Style Transfer. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 2915–2924, Online. Association for Computational Linguistics.
- Cite (Informal):
- Contextual Text Style Transfer (Cheng et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2020.findings-emnlp.263.pdf
- Data
- GYAFC