Towards Fine-grained Text Sentiment Transfer
Fuli Luo, Peng Li, Pengcheng Yang, Jie Zhou, Yutong Tan, Baobao Chang, Zhifang Sui, Xu Sun
Abstract
In this paper, we focus on the task of fine-grained text sentiment transfer (FGST). This task aims to revise an input sequence to satisfy a given sentiment intensity, while preserving the original semantic content. Different from the conventional sentiment transfer task that only reverses the sentiment polarity (positive/negative) of text, the FTST task requires more nuanced and fine-grained control of sentiment. To remedy this, we propose a novel Seq2SentiSeq model. Specifically, the numeric sentiment intensity value is incorporated into the decoder via a Gaussian kernel layer to finely control the sentiment intensity of the output. Moreover, to tackle the problem of lacking parallel data, we propose a cycle reinforcement learning algorithm to guide the model training. In this framework, the elaborately designed rewards can balance both sentiment transformation and content preservation, while not requiring any ground truth output. Experimental results show that our approach can outperform existing methods by a large margin in both automatic evaluation and human evaluation.- Anthology ID:
- P19-1194
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2013–2022
- Language:
- URL:
- https://aclanthology.org/P19-1194
- DOI:
- 10.18653/v1/P19-1194
- Cite (ACL):
- Fuli Luo, Peng Li, Pengcheng Yang, Jie Zhou, Yutong Tan, Baobao Chang, Zhifang Sui, and Xu Sun. 2019. Towards Fine-grained Text Sentiment Transfer. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2013–2022, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Towards Fine-grained Text Sentiment Transfer (Luo et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/P19-1194.pdf
- Code
- luofuli/Fine-grained-Sentiment-Transfer