NLP seminar talk by Julia Kreuzter (Google)

Title

Tackling Low-Resource Machine Translation with Participation, Data and Scale

Abstract

This talk will feature three aspects that have recently changed the landscape for low-resource machine translation: First, we'll discover the role of participatory approaches that place native speakers at the core of the development, with the Masakhane community as an example for African languages. Second, we'll dive deep into quality issues of multilingual public datasets that affect low-resource languages disproportionately. And last, we'll learn about the tricks behind Google Translate's most recent success in launching NMT for languages without any parallel data.

Bio

Julia Kreutzer is a Research Scientist at Google Montreal, where she works on improving machine translation. She holds a PhD in Computational Linguistics from Heidelberg University, Germany, and has also been working with the Masakhane community to develop NLP technologies for African languages and making NLP more accessible. Her current research focuses on the characteristics and balancing of data for machine translation.