Decode with Template: Content Preserving Sentiment Transfer

Zhiyuan Wen, Jiannong Cao, Ruosong Yang, Senzhang Wang


Abstract
Sentiment transfer aims to change the underlying sentiment of input sentences. The two major challenges in existing works lie in (1) effectively disentangling the original sentiment from input sentences; and (2) preserving the semantic content while transferring the sentiment. We find that identifying the sentiment-irrelevant content from input sentences to facilitate generating output sentences could address the above challenges and then propose the Decode with Template model in this paper. We first mask the explicit sentiment words in input sentences and use the rest parts as templates to eliminate the original sentiment. Then, we input the templates and the target sentiments into our bidirectionally guided variational auto-encoder (VAE) model to generate output. In our method, the template preserves most of the semantics in input sentences, and the bidirectionally guided decoding captures both forward and backward contextual information to generate output. Both two parts contribute to better content preservation. We evaluate our method on two review datasets, Amazon and Yelp, with automatic evaluation methods and human rating. The experimental results show that our method significantly outperforms state-of-the-art models, especially in content preservation.
Anthology ID:
2020.lrec-1.575
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4671–4679
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.575
DOI:
Bibkey:
Cite (ACL):
Zhiyuan Wen, Jiannong Cao, Ruosong Yang, and Senzhang Wang. 2020. Decode with Template: Content Preserving Sentiment Transfer. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4671–4679, Marseille, France. European Language Resources Association.
Cite (Informal):
Decode with Template: Content Preserving Sentiment Transfer (Wen et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.575.pdf