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Marcin Wróblewski

Researcher at Boys Town

Publications -  14
Citations -  336

Marcin Wróblewski is an academic researcher from Boys Town. The author has contributed to research in topics: Noise & Loudness. The author has an hindex of 4, co-authored 12 publications receiving 292 citations. Previous affiliations of Marcin Wróblewski include City University of New York & New York University.

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Journal ArticleDOI

Combined effects of noise and reverberation on speech recognition performance of normal-hearing children and adults.

TL;DR: Results support the importance of attention to classroom acoustics and emphasize the need for maximizing SNR in classrooms, especially in classrooms designed for early childhood grades.
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Effects of reverberation on speech recognition in stationary and modulated noise by school-aged children and young adults.

TL;DR: The overall pattern suggests that younger children require better acoustic conditions to achieve sentence recognition equivalent to their older peers and adults, and supports the importance of minimizing noise and reverberation in classrooms.
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A meta-analysis of outcomes of hydration intervention on phonation threshold pressure.

TL;DR: A comprehensive meta-analysis of the effects of superficial and systemic vocal fold hydration on phonation threshold pressure (PTP), a measure of efficiency of voice production, found that, overall, hydration treatment demonstrated a tendency to reduce PTP.
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Measuring Speech Recognition in Children With Cochlear Implants in a Virtual Classroom

TL;DR: Direct connect testing with reverberant test materials allows assessment of speech recognition under conditions typical of classrooms and could be useful in identifying children with CIs whose performance decreases significantly in the presence of reverberation and noise.
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Deriving loudness growth functions from categorical loudness scaling data.

TL;DR: The goal of this study was to reconcile the differences between measures of loudness obtained with continuous, unbounded scaling procedures, and those obtained using a limited number of discrete categories, such as categorical loudness scaling (CLS).