@conference {10.1007/978-3-031-95582-2_12,
	title = {Automated Segmentation of Polish Sibilants Using Modified YAMNet Architecture for Computer-Aided Speech Diagnosis in Children},
	booktitle = {Information Technology in Biomedicine},
	year = {2025},
	pages = {144{\textendash}154},
	publisher = {Springer Nature Switzerland},
	organization = {Springer Nature Switzerland},
	address = {Cham},
	abstract = {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{\%}.},
	isbn = {978-3-031-95582-2},
	doi = {10.1007/978-3-031-95582-2_12},
	author = {Kr{\k e}cichwost, Micha{\l} and Badura, Pawe{\l} and Piet, Artur and Hasan, Md Abid and Mo{\'c}ko, Natalia and Miodo{\'n}ska, Zuzanna and Sage, Agata and Grzegorzek, Marcin},
	editor = {Badura, Pawel and Czajkowska, Joanna and Gertych, Arkadiusz and Kawa, Jacek and Pi{\k e}tka, Ewa and Wieclawek, Wojciech}
}
