Experiments with discourse-level choices and readability

This paper reports on pilot experiments that are being used, together with corpus analysis, in the development of a Natural Language Generation (NLG) system, GIRL (Generator for Individual Reading Levels). GIRL generates reports for individuals after a literacy assessment. We tested GIRL's output on adult learner readers and good readers. Our aim was to find out if choices the system makes at the discourse-level have an impact on readability. Our preliminary results indicate that such choices do indeed appear to be important for learner readers. These will be investigated further in future larger-scale experiments. Ultimately we intend to use the results to develop a mechanism that makes discourse-level choices that are appropriate for individuals' reading skills

Reading errors made by skilled and unskilled readers: evaluating a system that generates reports for people with poor literacy

This study evaluates a natural language generation system that creates literacy assessment reports in order to create more readable documents. Prior research assessed comprehension and reading speed on modified documents. Here, we investigate whether individuals make less reading errors after the system modifies documents to make them more readable. Preliminary results show that poor readers make more errors than good readers. The full paper will describe readers' rates of errors on documents modified for readability

A corpus analysis of discourse relations for Natural Language Generation

We are developing a Natural Language Generation (NLG) system that generates texts tailored for the reading ability of individual readers. As part of building the system, GIRL (Generator for Individual Reading Levels), we carried out an analysis of the RST Discourse Treebank Corpus to find out how human writers linguistically realise discourse relations. The goal of the analysis was (a) to create a model of the choices that need to be made when realising discourse relations, and (b) to understand how these choices were typically made for “normal” readers, for a variety of discourse relations. We present our results for discourse relations: concession, condition, elaboration additional, evaluation, example, reason and restatement. We discuss the results and how they were used in GIRL

Generating readable texts for readers with low basic skills

Most NLG systems generate texts for readers with good reading ability, but SkillSum adapts its output for readers with poor literacy. Evaluation with lowskilled readers confirms that SkillSum's knowledge-based microplanning choices enhance readability. We also discuss future readability improvements

Acquiring Correct Knowledge for Natural Language Generation

Natural language generation (NLG) systems are computer software systems that produce texts in English and other human languages, often from non-linguistic input data. NLG systems, like most AI systems, need substantial amounts of knowledge. However, our experience in two NLG projects suggests that it is difficult to acquire correct knowledge for NLG systems; indeed, every knowledge acquisition (KA) technique we tried had significant problems. In general terms, these problems were due to the complexity, novelty, and poorly understood nature of the tasks our systems attempted, and were worsened by the fact that people write so differently. This meant in particular that corpus-based KA approaches suffered because it was impossible to assemble a sizable corpus of high-quality consistent manually written texts in our domains; and structured expert-oriented KA techniques suffered because experts disagreed and because we could not get enough information about special and unusual cases to build robust systems. We believe that such problems are likely to affect many other NLG systems as well. In the long term, we hope that new KA techniques may emerge to help NLG system builders. In the shorter term, we believe that understanding how individual KA techniques can fail, and using a mixture of different KA techniques with different strengths and weaknesses, can help developers acquire NLG knowledge that is mostly correct

Does splitting make sentence easier?

In this study, we focus on sentence splitting, a subfield of text simplification, motivated largely by an unproven idea that if you divide a sentence in pieces, it should become easier to understand. Our primary goal in this study is to find out whether this is true. In particular, we ask, does it matter whether we break a sentence into two, three, or more? We report on our findings based on Amazon Mechanical Turk. More specifically, we introduce a Bayesian modeling framework to further investigate to what degree a particular way of splitting the complex sentence affects readability, along with a number of other parameters adopted from diverse perspectives, including clinical linguistics, and cognitive linguistics. The Bayesian modeling experiment provides clear evidence that bisecting the sentence leads to enhanced readability to a degree greater than when we create simplification with more splits

Lectura para todos: el aporte de la fácil lectura como vía para la equiparación de oportunidades

"Lectura para todos" es una obra esencial dentro del diálogo establecido por especialistas del ámbito donde se pone de manifiesto la necesidad de llevar a cabo los cambios inevitables ante el discurso teórico y recurrente de la igualdad de oportunidades. Una forma fundamental de conocer cómo mejorar el hábito lector y cómo entrenar la competencia lectoras al albor de los numerosos estudios que demuestran que obteniendo buenos resultados en objetivos básicos de estas dos manifestaciones culturales de la lectura se puede equilibrar justamente la igualdad de oportunidades; donde no podemos olvidar el caso de Alemania cuando en 2002 puntuó en los informes PISA por debajo de la media y pusieron en marcha un plan de “rescate” lector a los que peor puntuaban y no un entrenamiento para mejorar a los que ya superaban la prueba. Nuestro agradecimiento al Núcleo de Investigación en Lectura Fácil y Educación Inclusiva de Chile por contar con la Asociación Española de Comprensión Lectora para compartir un espacio donde crear sinergias en el ámbito de la lectura: el hábito lector y la competencia lectoras