Papers Text Simplification

Book Review: Automatic Text Simplification by Horacio Saggion

Sentence Packaging in Text Generation from Semantic Graphs as a Community Detection Problem

An increasing amount of research tackles the challenge of text generation from abstract ontological or semantic structures, which are in their very nature potentially large connected graphs. These graphs must be {``}pack…

The Interface Between Readability and Automatic Text Simplification

CLEAR -- Simple Corpus for Medical French

Assisted Lexical Simplification for French Native Children with Reading Difficulties

Improving Machine Translation of English Relative Clauses with Automatic Text Simplification

Integrating Transformer and Paraphrase Rules for Sentence Simplification

Sentence simplification aims to reduce the complexity of a sentence while retaining its original meaning. Current models for sentence simplification adopted ideas from ma- chine translation studies and implicitly learned…

Unsupervised Neural Text Simplification

The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora. The core framework is composed of a shared encoder and a pair of attentional-decoders and gai…

Large-scale Hierarchical Alignment for Data-driven Text Rewriting

We propose a simple unsupervised method for extracting pseudo-parallel monolingual sentence pairs from comparable corpora representative of two different text styles, such as news articles and scientific papers. Our appr…

BLEU is Not Suitable for the Evaluation of Text Simplification

BLEU is widely considered to be an informative metric for text-to-text generation, including Text Simplification (TS). TS includes both lexical and structural aspects. In this paper we show that BLEU is not suitable for …

Simple and Effective Text Simplification Using Semantic and Neural Methods

Sentence splitting is a major simplification operator. Here we present a simple and efficient splitting algorithm based on an automatic semantic parser. After splitting, the text is amenable for further fine-tuned simpli…

Semantic Structural Evaluation for Text Simplification

Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects. In this paper we propose the first measure to address structural aspects of text si…

Improving Neural Text Simplification Model with Simplified Corpora

Text simplification (TS) can be viewed as monolingual translation task, translating between text variations within a single language. Recent neural TS models draw on insights from neural machine translation to learn lexi…

Identification of Parallel Sentences in Comparable Monolingual Corpora from Different Registers

Parallel aligned sentences provide useful information for different NLP applications. Yet, this kind of data is seldom available, especially for languages other than English. We propose to exploit comparable corpora in F…

An Unsupervised System for Parallel Corpus Filtering

In this paper we describe LMU Munich{'}s submission for the \textit{WMT 2018 Parallel Corpus Filtering} shared task which addresses the problem of cleaning noisy parallel corpora. The task of mining and cleaning parallel…

Monolingual sentence matching for text simplification

This work improves monolingual sentence alignment for text simplification, specifically for text in standard and simple Wikipedia. We introduce a convolutional neural network structure to model similarity between two sen…

Demonstrating PAR4SEM - A Semantic Writing Aid with Adaptive Paraphrasing

In this paper, we present Par4Sem, a semantic writing aid tool based on adaptive paraphrasing. Unlike many annotation tools that are primarily used to collect training examples, Par4Sem is integrated into a real word app…

Lexi: A tool for adaptive, personalized text simplification

Most previous research in text simplification has aimed to develop generic solutions, assuming very homogeneous target audiences with consistent intra-group simplification needs. We argue that this assumption does not ho…

Modeling the Readability of German Targeting Adults and Children: An empirically broad analysis and its cross-corpus validation

We analyze two novel data sets of German educational media texts targeting adults and children. The analysis is based on 400 automatically extracted measures of linguistic complexity from a wide range of linguistic domai…

Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs

Complexity of texts is usually assessed only at the lexical and syntactic levels. Although it is known that conceptual complexity plays a significant role in text understanding, no attempts have been made at assessing it…