Lexical Simplification is the task of replacing individual words of a text with words that are easier to understand, so that the text as a whole becomes easier to comprehend, e.g. by people with learning disabilities or by children who learn to read. Although this seems like a straightforward task, evaluating algorithms for this task is not so. The problem is how to build a dataset that provide...

Natural Language Processing Tools for Reading Level Assessment and Text Simplification for Bilingual Education

In this pa per we present an automatic text simplification system for Spanish which intends to make texts more accessible for users with cognitive disabilities. This system aims at reducing the structural complexity of Spanish sentences in that it converts complex sentences in two or more simple sentences and therefore reduces reading difficulty.

In this paper we discuss particular choices we made during the development of a rule-based syntactic text simplification system. Such choices concern 1) how to deal with adverbial phrases in order to simplify sentences, and 2) the order in which to apply our set of simplification rules. Adverbial phrases have not been considered by previous work on text simplification, but have a considerable i...

Lexical Simplification consists in replacing complex words in a text with simpler alternatives. We introduce LEXenstein, the first open source framework for Lexical Simplification. It covers all major stages of the process and allows for easy benchmarking of various approaches. We test the tool’s performance and report comparisons on different datasets against the state of the art approaches. T...

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, and provide commentary to aid readers in reaching the correct interpretation. We introduce the task of automated lyric annotation (ALA). Like text simplification, a goal of ALA i...

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 of word embeddings and paraphrase lexicons. Through an empirical experiment using the QATS dataset (Štajner et al., 2016b), we confirm that we can achieve the state-of-the-art ...

We introduce a bootstrapping algorithm for regression that exploits word embedding models. We use it to infer four psycholinguistic properties of words: Familiarity, Age of Acquisition, Concreteness and Imagery and further populate the MRC Psycholinguistic Database with these properties. The approach achieves 0.88 correlation with humanproduced values and the inferred psycholinguistic features ...

Text simplification involves restructuring sentences by replacing particular syntactic constructs (like embedded clauses and appositives). The aim is to make the text easier to read for some target group (like aphasics and people with low reading ages) or easier to process by some program (like a parser or machine translation system). However, sentencelevel syntactic restructuring can wreak hav...

This paper introduces Japanese lexical simplification. Japanese lexical simplification is the task of replacing complex words in a given sentence with simple words to produce a new sentence without changing the original meaning of the sentence. We propose a method of supervised regression learning to estimate complexity ordering of words with statistical features obtained from two types of Japa...