Papers Text Simplification

Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification

This paper examines the usefulness of semantic features based on word alignments for estimating the quality of text simplification. Specifically, we introduce seven types of alignment-based features computed on the basis…

MUSST: A Multilingual Syntactic Simplification Tool

We describe MUSST, a multilingual syntactic simplification tool. The tool supports sentence simplifications for English, Italian and Spanish, and can be easily extended to other languages. Our implementation includes a s…

A Semantic Relevance Based Neural Network for Text Summarization and Text Simplification

Text summarization and text simplification are two major ways to simplify the text for poor readers, including children, non-native speakers, and the functionally illiterate. Text summarization is to produce a brief summ…

Framework for the Analysis of Simplified Texts Taking Discourse into Account: the Basque Causal Relations as Case Study

From Shakespeare to Twitter: What are Language Styles all about?

As natural language processing research is growing and largely driven by the availability of data, we expanded research from news and small-scale dialog corpora to web and social media. User-generated data and crowdsourc…

Combining Multiple Corpora for Readability Assessment for People with Cognitive Disabilities

Given the lack of large user-evaluated corpora in disability-related NLP research (e.g. text simplification or readability assessment for people with cognitive disabilities), the question of choosing suitable training da…

Simplifying metaphorical language for young readers: A corpus study on news text

The paper presents first results of an ongoing project on text simplification focusing on linguistic metaphors. Based on an analysis of a parallel corpus of news text professionally simplified for different grade levels,…

Using Gaze to Predict Text Readability

We show that text readability prediction improves significantly from hard parameter sharing with models predicting first pass duration, total fixation duration and regression duration. Specifically, we induce multi-task …

An Adaptable Lexical Simplification Architecture for Major Ibero-Romance Languages

Lexical Simplification is the task of reducing the lexical complexity of textual documents by replacing difficult words with easier to read (or understand) expressions while preserving the original meaning. The developme…

Splitting Complex English Sentences

This paper applies parsing technology to the task of syntactic simplification of English sentences, focusing on the identification of text spans that can be removed from a complex sentence. We report the most comprehensi…

CLaC @ QATS: Quality Assessment for Text Simplification

This paper describes our approach to the 2016 QATS quality assessment shared task. We trained three independent Random Forest classifiers in order to assess the quality of the simplified texts in terms of grammaticality,…

Automatic Identification of AltLexes using Monolingual Parallel Corpora

The automatic identification of discourse relations is still a challenging task in natural language processing. Discourse connectives, such as "since" or "but", are the most informative cues to identify explicit relation…

Break it Down for Me: A Study in Automated Lyric Annotation

Comprehending lyrics, as found in songs and poems, can pose a challenge to human and machine readers alike. This motivates the need for systems that can understand the ambiguity and jargon found in such creative texts, a…

Exploring Neural Text Simplification Models

We present the first attempt at using sequence to sequence neural networks to model text simplification (TS). Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to …

Sentence Alignment Methods for Improving Text Simplification Systems

We provide several methods for sentence-alignment of texts with different complexity levels. Using the best of them, we sentence-align the Newsela corpora, thus providing large training materials for automatic text simpl…

A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese

Psycholinguistic properties of words have been used in various approaches to Natural Language Processing tasks, such as text simplification and readability assessment. Most of these properties are subjective, involving c…

Services for text simplification and analysis

A Semantic QA-Based Approach for Text Summarization Evaluation

Many Natural Language Processing and Computational Linguistics applications involves the generation of new texts based on some existing texts, such as summarization, text simplification and machine translation. However, …

Psycholinguistic Models of Sentence Processing Improve Sentence Readability Ranking

While previous research on readability has typically focused on document-level measures, recent work in areas such as natural language generation has pointed out the need of sentence-level readability measures. Much of p…

Sentence Simplification with Deep Reinforcement Learning

Sentence simplification aims to make sentences easier to read and understand. Most recent approaches draw on insights from machine translation to learn simplification rewrites from monolingual corpora of complex and simp…