arXiv Open Access 2018

A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification

Mounica Maddela Wei Xu
Lihat Sumber

Abstrak

Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity lexicon of 15,000 English words and propose a novel neural readability ranking model with a Gaussian-based feature vectorization layer that utilizes these human ratings to measure the complexity of any given word or phrase. Our model performs better than the state-of-the-art systems for different lexical simplification tasks and evaluation datasets. Additionally, we also produce SimplePPDB++, a lexical resource of over 10 million simplifying paraphrase rules, by applying our model to the Paraphrase Database (PPDB).

Topik & Kata Kunci

Penulis (2)

M

Mounica Maddela

W

Wei Xu

Format Sitasi

Maddela, M., Xu, W. (2018). A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification. https://arxiv.org/abs/1810.05754

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2018
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓