Katharina Kann

Institute of Cognitive Sciences – University of Colorado

Natural language processing (NLP) plays an increasingly important role in everyday life, and many people are familiar with products such as Google Translate, Alexa or Siri. However, NLP systems currently only exist for a small fraction of the world’s approximately 7000 languages. This is undesirable for many reasons: For instance, only speakers of high-resource languages are able to benefit from the abundance of information available on the internet, which reinforces already existing inequalities. It also limits the ability of NLP to support language documentation and revitalization efforts. 

In my talk, I will present NLP research focused explicitly on low-resource languages. I will first talk about how we can leverage NLP systems to speed up language documentation efforts. I will then discuss how existing pretrained multilingual models can be adapted to truly low-resource languages.