DAIRSACC - Do Acronyms Influence Reading Speed and Content Comprehension?

Acronyms, initialisms and other types of abbreviations are frequently used in scientific, academic, governmental and administrative setting to shorten lengthy terminology and nomenclature. While they can make a text easier to read for people familiar with the abbreviations, they can add to the text's inherent difficulty and impede comprehension for those who are not familiar with their meaning. The phenomenon of acronym polynymy (multiple definitions associated with the same acronym) can create confusion and add to the cognitive load associated with understanding the text. The current practice of defining acronyms only once, when introduced can result in readers scrolling back and forth in the text looking for acronym definitions, increasing the cognitive load and negatively affect reading speed and content comprehension. The purpose of this research was to study if the presence of a large number of acronyms in a text impedes reading performance. The current study also investigated if providing easy access to acronym definitions via hover text would alleviate comprehension problems caused by unknown acronyms in the text. The hypothesis was that by enabling fast acronym disambiguation, and eliminating the need to scroll for acronym definitions, the hover functionality would enhance reading speed and content comprehension. The results of the experiment are analyzed and recommendations for future investigations of the acronym problem are formulated

CLARIN

The book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium

CLARIN. The infrastructure for language resources

CLARIN, the "Common Language Resources and Technology Infrastructure", has established itself as a major player in the field of research infrastructures for the humanities. This volume provides a comprehensive overview of the organization, its members, its goals and its functioning, as well as of the tools and resources hosted by the infrastructure. The many contributors representing various fields, from computer science to law to psychology, analyse a wide range of topics, such as the technology behind the CLARIN infrastructure, the use of CLARIN resources in diverse research projects, the achievements of selected national CLARIN consortia, and the challenges that CLARIN has faced and will face in the future. The book will be published in 2022, 10 years after the establishment of CLARIN as a European Research Infrastructure Consortium by the European Commission (Decision 2012/136/EU)

CLARIN

The book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium

Tune your brown clustering, please

Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly unexplored. Accordingly, we present information for practitioners on the behaviour of Brown clustering in order to assist hyper-parametre tuning, in the form of a theoretical model of Brown clustering utility. This model is then evaluated empirically in two sequence labelling tasks over two text types. We explore the dynamic between the input corpus size, chosen number of classes, and quality of the resulting clusters, which has an impact for any approach using Brown clustering. In every scenario that we examine, our results reveal that the values most commonly used for the clustering are sub-optimal

Play Among Books

How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme

Computational Linguistics; Germanic Languages; Artificial Intelligence (incl. Robotics); Computing Methodologie