Text Simplification

Text simplification aims to rewrite text into simpler versions, and thus make information accessible to a broader audience. Most pre- vious work simplifies sentences using hand- crafted rules aimed at …...

AbstractText simplification is the process of reducing the lexical and syntactic complexity of a text while attempting to preserve (most of) its information content. It has recently emerged as an …...

AbstractIn this paper we describe the development of a text simplification system for Spanish. Text simplification is the adaptation of a text to the special needs of certain groups of …...

The occurrence of syntactic phenomena such as coordination and subordination is characteristic of long, complex sentences. Text simplification systems need to detect and categorise constituents in order to generate simpler …...

In this paper we examine language mod- eling for text simplification. Unlike some text-to-text translation tasks, text simplifi- cation is a monolingual translation task al- lowing for text in both …...

While the automatic analysis of the read- ability of texts has a long history, the use of readability assessment for text simplifi- cation has received only little attention so far. …...

We present an approach to text simplifi- cation based on synchronous dependency grammars. The higher level of abstraction afforded by dependency representations allows for a linguistically sound treatment of complex …...

We describe two systems for text simplification using typed dependency structures, one that performs lexical and syntactic simplification, and another that performs sentence compression optimised to satisfy global text constraints …...

This work improves monolingual sentence alignment for text simplification, specifically for text in standard and simple Wikipedia. We introduce a method that improves over past efforts by using a greedy …...

In recent years, several studies have ap- proached the Text Simplification (TS) task as a machine translation (MT) problem. They report promising results in learning how to translate from ‘original’ …...

AbstractMethods for text simplification using the framework of statistical machine translation have been extensively studied in recent years. However, building the monolingual parallel corpus necessary for training the model requires …...

AbstractMost recent sentence simplification systems use basic machine translation models to learn lexical and syntactic paraphrases from a manually simplified parallel corpus. These methods are limited by the quality and …...

AbstractSentence compression is a way to perform text simplification and is usually handled in a monolingual setting. In this paper, we study ways to extend sentence compression in a bilingual …...

In text simplification (TS), parallel corpora consisting of original sentences and their manually simplified counterparts are very scarce and small in size, which impedes building supervised automated TS systems with …...

Tasks such as knowledge extraction, text simplification and summarization have in common the fact that from a text fragment a smaller (not necessarily contiguous) portion is obtained by discarding part …...

We attempted to generate a sentence by using the concept of core vocabulary whilst preserv- ing the original meaning of the sentence in the text simplification subtask. The correlation between …...

AbstractLearning from a real-world data stream and continuously updating the model without explicit supervision is a new challenge for NLP applications with machine learning components. In this work, we have …...

The lack of large and reliable datasets has been hindering progress in Text Simplification (TS). We investigate the application of the recently created Newsela corpus, the largest collection of professionally …...

AbstractAutomatically generating animation from natural language text finds application in a number of areas e.g. movie script writing, instructional videos, and public safety. However, translating natural language text into animation …...

AbstractWe 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 approach …...

AbstractParaphrase generation can be regarded as monolingual translation. Unlike bilingual machine translation, paraphrase generation rewrites only a limited portion of an input sentence. Hence, previous methods based on machine translation …...

We propose a modular rule-based system for Text Simplification and show that it out- performs the state-of-the-art neural-based simplification system in terms of simplic- ity. We compare the output of …...

AbstractIn this paper, we present a corpus for use in automatic readability assessment and automatic text simplification for German, the first of its kind for this language. The corpus is …...

AbstractThe goal of text simplification (TS) is to transform difficult text into a version that is easier to understand and more broadly accessible to a wide variety of readers. In …...

AbstractText simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical. It is often considered an all-purpose generic …...

AbstractMultiword expressions (MWEs) represent lexemes that should be treated as single lexical units due to their idiosyncratic nature. Multiple NLP applications have been shown to benefit from MWE identification, however …...

AbstractWe present FELIX – a flexible text-editing approach for generation, designed to derive maximum benefit from the ideas of decoding with bi-directional contexts and self-supervised pretraining. In contrast to conventional …...

AbstractThe success of a text simplification system heavily depends on the quality and quantity of complex-simple sentence pairs in the training corpus, which are extracted by aligning sentences between parallel …...

AbstractWe propose Seq2Edits, an open-vocabulary approach to sequence editing for natural language processing (NLP) tasks with a high degree of overlap between input and output texts. In this approach, each …...

AbstractText Simplification improves the readability of sentences through several rewriting transformations, such as lexical paraphrasing, deletion, and splitting. Current simplification systems are predominantly sequence-to-sequence models that are trained end-to-end to …...

AbstractText simplification is a valuable technique. However, current research is limited to sentence simplification. In this paper, we define and investigate a new task of document-level text simplification, which aims …...

AbstractText simplification reduces the language complexity of professional content for accessibility purposes. End-to-end neural network models have been widely adopted to directly generate the simplified version of input text, usually …...

Modern text simplification (TS) heavily relies on the availability of gold standard data to build machine learning models. However, ex- isting studies show that parallel TS corpora contain inaccurate simplifications …...

AbstractJudging the readability of text has many important applications, for instance when performing text simplification or when sourcing reading material for language learners. In this paper, we present a 518 …...

AbstractText Simplification (TS) is the task of converting a text into a form that is easier to read while maintaining the meaning of the original text. A sub-task of TS …...

AbstractText simplification is a method for improving the accessibility of text by converting complex sentences into simple sentences. Multiple studies have been done to create datasets for text simplification. However, …...

AbstractComplex word identification (CWI) is a cornerstone process towards proper text simplification. CWI is highly dependent on context, whereas its difficulty is augmented by the scarcity of available datasets which …...

AbstractIterative text revision improves text quality by fixing grammatical errors, rephrasing for better readability or contextual appropriateness, or reorganizing sentence structures throughout a document. Most recent research has focused on …...

AbstractTraditionally, Text Simplification is treated as a monolingual translation task where sentences between source texts and their simplified counterparts are aligned for training. However, especially for longer input documents, summarizing …...

. Interest in automatic closed captioning systems has risen on account of legal obli- gations concerning accessibility and the sheer amount of audiovisual content being produced by multiple sources. Such …...

AbstractAccess to higher education is critical for minority populations and emergent bilingual students. However, the language used by higher education institutions to communicate with prospective students is often too complex; …...

AbstractThis project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate …...

AbstractIn the age of knowledge, the democratisation of information facilitated through the Internet may not be as pervasive if written language poses challenges to particular sectors of the population. The …...

AbstractText simplification is an intralingual translation task in which documents, or sentences of a complex source text are simplified for a target audience. The success of automatic text simplification systems …...

AbstractOne of the major problems with text simplification is the lack of high-quality data. The sources of simplification datasets are limited to Wikipedia and Newsela, restricting further development of this …...