deepQuest-py: Large and Distilled Models for Quality Estimation

Abstract

We introduce deepQuest-py, a framework for training and evaluation of large and light-weight models for Quality Estimation (QE). deepQuest-py provides access to (1) state-of-the-art models based on pre-trained Transformers for sentence-level and word-level QE; (2) light-weight and efficient sentence-level models implemented via knowledge distillation; and (3) a web interface for testing models and visualising their predictions. deepQuest-py is available at https://github.com/sheffieldnlp/deepQuest-py under a CC BY-NC-SA licence.

Publication
EMNLP 2021: System Demonstrations (Accepted)
Fernando Alva-Manchego
Fernando Alva-Manchego
Research Associate

My research interests include text simplification, readability assessment, evaluation of natural language generation, and writing assistance.