Modeling Five Sentence Quality Representations by Finding Latent Spaces Produced with Deep Long Short-Memory Models
Pablo Rivas · Meeting of the Association for Computational Linguistics · 2019
We present a study in which we train neural models that approximate rules that assess the quality of English sentences. We modeled five rules using deep LSTMs trained over a dataset of sentences whose quality is evaluated under such rules. Preliminary results suggest the neural architecture can model such rules to high accuracy.