The NTNU-YZU System in the AESW Shared Task: Automated Evaluation of Scientific Writing Using a Convolutional Neural Network
Lung‐Hao Lee, Bo-Lin Lin, Liang-Chih Yu, Yuen‐Hsien Tseng · 2016
This study describes the design of the NTNU-YZU system for the automated evaluation of scientific writing shared task.We employ a convolutional neural network with the Word2Vec/GloVe embedding representation to predict whether a sentence needs language editing.For the Boolean prediction track, our best F-score of 0.6108 ranked second among the ten submissions.Our system also achieved an F-score of 0.7419 for the probabilistic estimation track, ranking fourth among the nine submissions.