Building a state-of-the-art approach to Grammatical Error Correction

Interview with the speaker

In this talk, we will look at the current state (post-BERT era) of GEC and share our experience of building the state-of-the-art system to perform this task. We will talk about the pros and cons of different architectures and compare inference times.

Kostiantyn Omelianchuk
Grammarly
  • Applied Research Scientist at Grammarly
  • Project lead and NLP expert with 4+ years of experience in the industry
  • 3rd-place winner of Home Depot Product Search Relevance competition on Kaggle (2016)
  • Currently working as Applied Research Scientist with the main focus on ensuring Grammarly leads the industry in Grammatical Error Correction
Oleksandr Skurzhanskyi
Grammarly
  • Applied Research Scientist at Grammarly
  • Works with the tasks of improving various aspects of communication that are beyond the scope of GEC
  • Interested in non-autoregressive sequence generation, self-supervised representation learning, and model compression techniques
  • Extensive experience in various NLP tasks like text simplification, machine translation, and geo-location extraction/recognition
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