Treffer: Hybridization of Acoustic and Visual Features of Polish Sibilants Produced by Children for Computer Speech Diagnosis.

Title:
Hybridization of Acoustic and Visual Features of Polish Sibilants Produced by Children for Computer Speech Diagnosis.
Authors:
Sage A; Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland., Miodońska Z; Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland., Kręcichwost M; Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland., Badura P; Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland.
Source:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 Aug 19; Vol. 24 (16). Date of Electronic Publication: 2024 Aug 19.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Imprint Name(s):
Original Publication: Basel, Switzerland : MDPI, c2000-
Comments:
Erratum in: Sensors (Basel). 2024 Dec 18;24(24):8061. doi: 10.3390/s24248061.. (PMID: 39771958)
References:
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Grant Information:
2018/30/E/ST7/00525 National Science Centre, Poland; 07/010/BK_24/1034 Polish Ministry of Science, Poland; Foundation for Polish Science (FNP)
Contributed Indexing:
Keywords: child speech; computer-assisted speech diagnosis; hybridization; sibilants; speech disorders; visual–audio features
Entry Date(s):
Date Created: 20240829 Date Completed: 20240829 Latest Revision: 20250205
Update Code:
20250205
PubMed Central ID:
PMC11359356
DOI:
10.3390/s24165360
PMID:
39205053
Database:
MEDLINE

Weitere Informationen

Speech disorders are significant barriers to the balanced development of a child. Many children in Poland are affected by lisps (sigmatism)-the incorrect articulation of sibilants. Since speech therapy diagnostics is complex and multifaceted, developing computer-assisted methods is crucial. This paper presents the results of assessing the usefulness of hybrid feature vectors extracted based on multimodal (video and audio) data for the place of articulation assessment in sibilants /s/ and /ʂ/. We used acoustic features and, new in this field, visual parameters describing selected articulators' texture and shape. Analysis using statistical tests indicated the differences between various sibilant realizations in the context of the articulation pattern assessment using hybrid feature vectors. In sound /s/, 35 variables differentiated dental and interdental pronunciation, and 24 were visual (textural and shape). For sibilant /ʂ/, we found 49 statistically significant variables whose distributions differed between speaker groups (alveolar, dental, and postalveolar articulation), and the dominant feature type was noise-band acoustic. Our study suggests hybridizing the acoustic description with video processing provides richer diagnostic information.