@inproceedings{95e55670d87246d3a861b3754161e750,
title = "Approach for spectrogram analysis in detection of selected pronunciation pathologies",
abstract = "An attempt to automatise selected pronunciation pathology detection in preschool children is described in this paper. Consonant [Z] in various phonetic surroundings is taken into consideration as eventual sigmatism indicator. The analysis involves spectrogram analysis in terms of image processing methods used for feature extraction and classification. Five dedicated features are defined and extracted, i.a., from a frequency sub-band of [1500, 6500] Hz. Binary classification using support vector machine enables pathology detection. The system performance is evaluated using sensitivity, specificity, and accuracy metrics in two cross-validation experiments over a database of 140 speech recordings with 50 normative and 90 pathological cases. Repeatable efficiency metrics at a ca. 85\% level confirm the method capabilities and encourage to develop the system for the speech diagnosis support.",
keywords = "Image processing, Spectrogram analysis, Speech pathology",
author = "Wojciech Bodusz and Zuzanna Miodo{\'n}ska and Pawe{\l} Badura",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; Conference on Innovations in Biomedical Engineering, IBE 2017 ; Conference date: 19-10-2017 Through 20-10-2017",
year = "2018",
doi = "10.1007/978-3-319-70063-2\_1",
language = "English",
isbn = "9783319700625",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "3--11",
editor = "Marek Gzik and Zbigniew Paszenda and Ewaryst Tkacz and Ewa Pietka",
booktitle = "Innovations in Biomedical Engineering",
address = "Germany",
}