Fernando Alva-Manchego

Fernando Alva-Manchego

Lecturer in Natural Language Processing
My research interests include text simplification, readability assessment, multilingual NLP, Welsh language technology, and NLP for education and social care.

Controllable Text Simplification with Explicit Paraphrasing

Text Simplification improves the readability of sentences through several rewriting transformations, such as lexical paraphrasing, deletion, and splitting. Current simplification …

mounica-maddela

Automatic Sentence Simplification with Multiple Rewriting Transformations

PhD Thesis

avatar
Fernando Alva-Manchego

ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations

We introduce ASSET, a dataset for assessing sentence simplification in English. ASSET is a crowdsourced multi-reference corpus where each simplification was produced by executing …

avatar
Fernando Alva-Manchego

Data-Driven Sentence Simplification: Survey and Benchmark

We survey research on Sentence Simplification, focusing on approaches that attempt to learn how to simplify using corpora of aligned original-simplified sentence pairs in English.

avatar
Fernando Alva-Manchego

EASSE: Easier Automatic Sentence Simplification Evaluation

We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification systems.

avatar
Fernando Alva-Manchego

Cross-Sentence Transformations in Text Simplification

WiNLP 2019

avatar
Fernando Alva-Manchego

Strong Baselines for Complex Word Identification across Multiple Languages

NAACL 2019

pierre-finnimore

MASSAlign: Alignment and Annotation of Comparable Documents

IJCNLP 2017: System Demonstrations

gustavo-paetzold

Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs

IJCNLP 2017

avatar
Fernando Alva-Manchego

Coh-Metrix-Esp: A Complexity Analysis Tool for Documents Written in Spanish

LREC 2016

andre-quispesaravia