Publication

Low-Resource Corpus Filtering using Multilingual Sentence Embeddings

Association for Computational Linguistics (ACL)


Abstract

In this paper, we describe our submission to the WMT19 low-resource parallel corpus filtering shared task. Our main approach is based on the LASER toolkit (Language-Agnostic SEntence Representations), which uses an encoder-decoder architecture trained on a parallel corpus to obtain multilingual sentence representations. We then use the representations directly to score and filter the noisy parallel sentences without additionally training a scoring function. We contrast our approach to other promising methods and show that LASER yields strong results. Finally, we produce an ensemble of different scoring methods and obtain additional gains. Our submission achieved the best overall performance for both the Nepali–English and Sinhala–English 1M tasks by a margin of 1.3 and 1.4 BLEU respectively, as compared to the second best systems. Moreover, our experiments show that this technique is promising for low and even no-resource scenarios.

Related Publications

All Publications

EMNLP - October 31, 2021

Evaluation Paradigms in Question Answering

Pedro Rodriguez, Jordan Boyd-Graber

NAACL - June 6, 2021

Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking

Zhaojiang Lin, Bing Liu, Seungwhan Moon, Paul Crook, Zhenpeng Zhou, Zhiguang Wang, Zhou Yu, Andrea Madotto, Eunjoon Cho, Rajen Subba

Uncertainty and Robustness in Deep Learning Workshop at ICML - June 24, 2021

DAIR: Data Augmented Invariant Regularization

Tianjian Huang, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami

EMNLP - November 16, 2020

Abusive Language Detection using Syntactic Dependency Graphs

Kanika Narang, Chris Brew

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy