Title
Filtering Pseudo-References by Paraphrasing for Automatic Evaluation of Machine Translation
Abstract
In this paper, we introduce our participation in the WMT 2019 Metric Shared Task. We propose a method to filter pseudo-references by paraphrasing for automatic evaluation of machine translation (MT). We use the outputs of off-the-shelf MT systems as pseudo-references filtered by paraphrasing in addition to a single human reference (gold reference). We use BERT fine-tuned with paraphrase corpus to filter pseudo-references by checking the paraphrasability with the gold reference. Our experimental results of the WMT 2016 and 2017 datasets show that our method achieved higher correlation with human evaluation than the sentence BLEU (Sent-BLEU) baselines with a single reference and with unfiltered pseudo-references.
Year
DOI
Venue
2019
10.18653/v1/w19-5360
FOURTH CONFERENCE ON MACHINE TRANSLATION (WMT 2019)
DocType
Citations 
PageRank 
Conference
1
0.35
References 
Authors
0
5
Name
Order
Citations
PageRank
Ryoma Yoshimura110.35
Hiroki Shimanaka210.35
Yukio Matsumura311.36
Hayahide Yamagishi410.35
Mamoru Komachi524144.56