Publication

WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia

Conference of the European Chapter of the Association for Computational Linguistics (EACL)


Abstract

We present an approach based on multilingual sentence embeddings to automatically extract parallel sentences from the content of Wikipedia articles in 96 languages, including several dialects or low-resource languages. We systematically consider all possible language pairs. In total, we are able to extract 135M parallel sentences for 1620 different language pairs, out of which only 34M are aligned with English. This corpus is freely available. To get an indication on the quality of the extracted bitexts, we train neural MT baseline systems on the mined data only for 1886 languages pairs, and evaluate them on the TED corpus, achieving strong BLEU scores for many language pairs. The WikiMatrix bitexts seem to be particularly interesting to train MT systems between distant languages without the need to pivot through English.

Related Publications

All Publications

EACL - April 20, 2021

FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary

Terra Blevins, Mandar Joshi, Luke Zettlemoyer

The Springer Series on Challenges in Machine Learning - December 12, 2019

The Second Conversational Intelligence Challenge (ConvAI2)

Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander Rudnicky, Jason Williams, Joelle Pineau, Jason Weston

ICLR - May 4, 2021

Combining Label Propagation and Simple Models Out-performs Graph Neural Networks

Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin Benson

ICLR - May 3, 2021

Creative Sketch Generation

Songwei Ge, Vedanuj Goswami, Larry Zitnick, Devi Parikh

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