Automated Grammatical Error Detection for Language Learners: Second Edition (Synthesis Lectures on Human Language Technologies) - Softcover

Críticas

“I can highly recommend this book to any reader who is interested in a short, readable overview of the state-of-the art in automated grammatical error detection, written by some of the most influential researchers in this field.” – Cornelia Tschichold for Linguist List

“The second edition of Automated Grammatical Error Detection for Language Learners provides exactly what the title promises, covering the state-of-the-art for grammatical error detection and correction for learner language data, with particular emphasis on English prepositions and articles...the book summarizes system design, gold standard annotation to support the task, and issues surrounding the evaluation of correction systems...Given the topics of the book, especially that of annotation, researchers working with learner corpora, and especially on the annotation of such corpora, can benefit greatly from reading this volume.” – Markus Dickinson, Indiana University

Reseña del editor

It has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well. These language learners provide a burgeoning market for tools that help identify and correct learners' writing errors. Unfortunately, the errors targeted by typical commercial proofreading tools do not include those aspects of a second language that are hardest to learn. This volume describes the types of constructions English language learners find most difficult: constructions containing prepositions, articles, and collocations. It provides an overview of the automated approaches that have been developed to identify and correct these and other classes of learner errors in a number of languages. Error annotation and system evaluation are particularly important topics in grammatical error detection because there are no commonly accepted standards. Chapters in the book describe the options available to researchers, recommend best practices for reporting results, and present annotation and evaluation schemes. The final chapters explore recent innovative work that opens new directions for research. It is the authors' hope that this volume will continue to contribute to the growing interest in grammatical error detection by encouraging researchers to take a closer look at the field and its many challenging problems.