14 papers · ranked by Valyu relevance
Scott Crossley, Joon Suh Choi, Kenny Tang, Laurie Cutting
This study documents and assesses the Tool for Automatic Analysis of Decoding Ambiguity (TAADA). TAADA calculates measures related to decoding, including metrics for grapheme and phoneme counts, neighborhood effects, rhymes, and conditional probabilities for sound-spelling relationships. These measures are assessed in…
Noa Handelsman, Dror Dotan
Number transcoding, the ability to convert digits to words and vice versa, is a critical skill in mathematical literacy and in everyday life. While transcoding is known to be difficult for children, it is unclear whether it challenges adults too, and if so, what the source of that difficulty is. Here, we analyzed the…
Katarzyna Chyl-Tanaś, Marcin Szczerbiński, Artur Pokropek, Joel Macoir
Highlights What are the main findings?1. • Good readers understood texts based on how well they understood spoken language, but struggling readers were held back by reading words too slowly and with too much effort. 2. • Adults who struggle with reading are not all the same. In our study, they fell into three groups…
Anna Chrabaszcz, Kailee Lear, Corrine Durisko, Julie Fiez
This study investigated whether adults with long-standing reading difficulties (“poor readers”) can acquire new literacy skills in both familiar (English pseudowords) and novel (artificial orthography, AO) systems, and how phonological decoding deficits relate to orthographic learning. Poor readers (n = 17) and matched…
Stéphane d’Ascoli, Corentin Bel, Jérémy Rapin, Hubert Banville + 3 more
While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) and magneto-encephalography (MEG) signals. We evaluate our approach on…
Chiara Pecini, Andrea Frascari, Viola Margheri, Kianna Kazemi + 2 more
The implementation of machine learning techniques enables the analysis of large data corpora to differentiate response patterns based on exercise parameters, providing insights for implementing efficient telerehabilitation of reading skills. In this study, we applied unsupervised machine learning methods to investigate…
Bartosz M. Radtke, Paweł Jurek, Michał Olech, Ariadna Łada-Maśko + 1 more
Introduction Translating dyslexia constructs to mild intellectual disability (MID) is challenging because population-based cut-offs may label broadly expected low attainment as ‘specific’. This study combined person-centered profiling with explicit, ICD-11-guided, severity-calibrated classification rules to quantify…
Ramis İleri, Çiğdem Gülüzar Altıntop, Fatma Latifoğlu, Esra Demirci
Dyslexia is a neurodevelopmental disorder that impairs reading, affecting 5-17.5% of children and representing the most common learning disability. Individuals with dyslexia experience decoding, reading fluency, and comprehension difficulties, hindering vocabulary development and learning. Early and accurate…
Meet Patel, Jonathan Ben Daniel, Nazim Bhimani, Anthony R. Glover + 2 more
Title: Simple Summary Liver surgery is complex and currently there are significant inconsistencies in determining the difficulty of a procedure. Most existing tools rely on operative time alone, which may not reflect the experience of the operator or unexpected challenges during surgery. This retrospective study aimed…
Apostolos Kargiotidis, George Manolitsis, Diamanto N. Filippatou
The present longitudinal retrospective study examined in a sample of 123 Greek-speaking children whether the raw score growth in a broad range of oral language and reading skills from Grade 1 to Grade 3 differs among children with persistent reading comprehension difficulties (pRCD; N = 49) identified in Grade 3, those…
Haodong Zhang, Wai Ting Siok, Nizhuan Wang, Wan-Young Chung
Imagined speech decoding has attracted growing interest in brain-computer interface (BCI) research, as it may enable language-related information to be recovered from non-overt neural activity. Current studies in this area are often treated as a single, unified research problem, despite substantial differences in…
Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu + 6 more
With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high-efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two-stage framework with high computational complexity and frequently struggle to…
Sara Conforti, Marialuisa Martelli, Pierluigi Zoccolotti, Chiara Valeria Marinelli + 1 more
Background/Objectives: Mastery of reading requires the ability to process multiple stimuli in sequence. Previous research shows that children gradually develop this skill as their reading experience increases. This study investigated the serial superiority effect and its association with reading experience. Reading…
Hsiang-Cheh Huang, Feng-Cheng Chang, Hong-Yi Li, Rabi N. Mahapatra + 1 more
With the proliferation of image-capturing and display-enabled IoT devices, ensuring the authenticity and integrity of visual data has become increasingly critical, especially in light of emerging cybersecurity threats and powerful generative AI tools. One of the major challenges in such sensor-based systems is the…