<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kręcichwost, Michał</style></author><author><style face="normal" font="default" size="100%">Badura, Paweł</style></author><author><style face="normal" font="default" size="100%">Piet, Artur</style></author><author><style face="normal" font="default" size="100%">Hasan, Md Abid</style></author><author><style face="normal" font="default" size="100%">Moćko, Natalia</style></author><author><style face="normal" font="default" size="100%">Miodońska, Zuzanna</style></author><author><style face="normal" font="default" size="100%">Sage, Agata</style></author><author><style face="normal" font="default" size="100%">Grzegorzek, Marcin</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Badura, Pawel</style></author><author><style face="normal" font="default" size="100%">Czajkowska, Joanna</style></author><author><style face="normal" font="default" size="100%">Gertych, Arkadiusz</style></author><author><style face="normal" font="default" size="100%">Kawa, Jacek</style></author><author><style face="normal" font="default" size="100%">Piętka, Ewa</style></author><author><style face="normal" font="default" size="100%">Wieclawek, Wojciech</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated Segmentation of Polish Sibilants Using Modified YAMNet Architecture for Computer-Aided Speech Diagnosis in Children</style></title><secondary-title><style face="normal" font="default" size="100%">Information Technology in Biomedicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer Nature Switzerland</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">144–154</style></pages><isbn><style face="normal" font="default" size="100%">978-3-031-95582-2</style></isbn><abstract><style face="normal" font="default" size="100%">In this paper, we address computer-aided speech diagnosis by designing a method for the automated detection of Polish sibilants in preschool children. Our database was recorded from 47 children aged four to seven using a 15-channel data acquisition device. We propose a modified YAMNet architecture to classify short speech segments from the main channel into four classes. The segments are represented by a dedicated acoustic image based on filter-bank energies and their derivatives. We use a set of time-series data augmentation procedures over the data from all microphones to improve training. With the segment classification results, we determine a frame-wise speech segmentation to extract sibilants. Our segment classification model yields overall accuracy of 87.9{%}, with the sibilant classification recall and precision at 92.3{%} and 87.7{%}, respectively. The sibilant segmentation accuracy reaches 96.2{%} with an F1 score of 73.5{%}.</style></abstract></record></records></xml>