To develop a Mandarin version of the Hearing in Noise Test for Children (MHINT-C) and examine the maturational effects on sentence recognition. Sentences suitable for evaluating children aged 6-18 years were selected from the adult MHINT to form 12 lists of 10 MHINT-C sentences (Study 1). List equivalence, inter-list reliability, response variability, and maturational effects on sentence recognition were examined using the MHINT-C (Study 2). A total of 246 children aged 6.1-17.11 years were included. Six children participated in Study 1; the rest were included in Study 2. To compare these results with adults, 20 native Mandarin-speaking adults aged 18 or above were included in Study 2. MHINT-C list equivalency, inter-list reliability, and response variability were similar to those of the adult MHINT and the Cantonese HINT for children. Sentence recognition in children reached adult-like performance around age 8 in quiet and at ages 15 and 14 in front and side noise conditions, respectively. The MHINT-C can reliably measure sentence recognition in quiet and noise in Mandarin-speaking children. Age-specific correction factors were established.
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Data Brief
February 2025
Department of Electrical, Electronic and Communication Engineering, Military Institute of Science and Technology (MIST), Dhaka 1216, Bangladesh.
The dataset represents a significant advancement in Bengali lip-reading and visual speech recognition research, poised to drive future applications and technological progress. Despite Bengali's global status as the seventh most spoken language with approximately 265 million speakers, linguistically rich and widely spoken languages like Bengali have been largely overlooked by the research community. fills this gap by offering a pioneering dataset tailored for Bengali lip-reading, comprising visual data from 150 speakers across 54 classes, encompassing Bengali phonemes, alphabets, and symbols.
View Article and Find Full Text PDFBehav Res Methods
January 2025
Department of Linguistics, University of Massachusetts, 650 North Pleasant Street, Amherst, MA, 01003, USA.
Eye tracking has been a popular methodology used to study the visual, cognitive, and linguistic processes underlying word recognition and sentence parsing during reading for several decades. However, the successful use of eye tracking requires researchers to make deliberate choices about how they apply this technique, and there is wide variability across labs and fields with respect to which choices are "standard." We aim to provide an easy-to-reference guideline that can help new researchers with their entrée into eye-tracking-while-reading research.
View Article and Find Full Text PDFMethodsX
June 2025
Computer Science Department, Information Technology University of Punjab, Lahore, Pakistan.
Optical character recognition (OCR) is vital in digitizing printed data into a digital format, which can be conveniently used for various purposes. A significant amount of work has been done in OCR for well-resourced languages like English. However, languages like Urdu, spoken by a large community, face limitations in OCR due to a lack of resources and the complexity and diversity of handwritten scripts.
View Article and Find Full Text PDFInt J Audiol
January 2025
Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, Leiden, Netherlands.
Objective: Measuring listening effort using pupillometry is challenging in cochlear implant (CI) users. We assess three validated speech tests (Matrix, LIST, and DIN) to identify the optimal speech material for measuring peak-pupil-dilation (PPD) in CI users as a function of signal-to-noise ratio (SNR).
Design: Speech tests were administered in quiet and two noisy conditions, namely at the speech recognition threshold (0 dB re SRT), i.
Acta Otolaryngol
January 2025
Department of Otolaryngology - Head & Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.
Background: There is conflicting literature regarding whether cochlear implants (CI) electrode array (EA) selection impacts audiologic outcomes.
Objective: To compare outcomes for the two EA designs, precurved and straight.
Methods: A systematic search of CINAHL, Cochrane Library, PubMed, and SCOPUS was conducted according to PRISMA guidelines.
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