Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity

Brian Thompson, Matt Post


Abstract
Recent work has shown that a multilingual neural machine translation (NMT) model can be used to judge how well a sentence paraphrases another sentence in the same language (Thompson and Post, 2020); however, attempting to generate paraphrases from such a model using standard beam search produces trivial copies or near copies. We introduce a simple paraphrase generation algorithm which discourages the production of n-grams that are present in the input. Our approach enables paraphrase generation in many languages from a single multilingual NMT model. Furthermore, the amount of lexical diversity between the input and output can be controlled at generation time. We conduct a human evaluation to compare our method to a paraphraser trained on the large English synthetic paraphrase database ParaBank 2 (Hu et al., 2019c) and find that our method produces paraphrases that better preserve meaning and are more gramatical, for the same level of lexical diversity. Additional smaller human assessments demonstrate our approach also works in two non-English languages.
Anthology ID:
2020.wmt-1.67
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
561–570
Language:
URL:
https://aclanthology.org/2020.wmt-1.67
DOI:
Bibkey:
Cite (ACL):
Brian Thompson and Matt Post. 2020. Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity. In Proceedings of the Fifth Conference on Machine Translation, pages 561–570, Online. Association for Computational Linguistics.
Cite (Informal):
Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity (Thompson & Post, WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.67.pdf
Video:
 https://slideslive.com/38939552
Code
 thompsonb/prism
Data
ParaBank