Modeling Five Sentence Quality Representations by Finding Latent Spaces Produced with Deep Long Short-Memory Models

Pablo Rivas


Abstract
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.
Anthology ID:
W19-3610
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WS | WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
24–26
Language:
URL:
https://www.aclweb.org/anthology/W19-3610
DOI:
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