Please use this identifier to cite or link to this item:
Title: Identification of Nasalization and Nasal Assimilation from Children’s Speech
Authors: Ramteke P.B.
Supanekar S.
Aithal V.
Koolagudi S.G.
Issue Date: 2020
Citation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , Vol. 11987 LNAI , , p. 244 - 253
Abstract: In children, nasalization is a commonly observed phonological process where the non-nasal sounds are substituted with nasal sounds. Here, an attempt has been made for the identification of nasalization and nasal assimilation. The properties of nasal sounds and nasalized voiced sounds are explored using MFCCs extracted from Hilbert envelope of the numerator of group delay (HNGD) Spectrum. HNGD Spectrum highlights the formants in the speech and extra nasal formant in the vicinity of first formant in nasalized voiced sounds. Features extracted from correctly pronounced and mispronounced words are compared using Dynamic Time Warping (DTW) algorithm. The nature of the deviation of DTW comparison path from its diagonal behavior is analyzed for the identification of mispronunciation. The combination of FFT based MFCCs and HNGD spectrum based MFCCs are observed to achieve highest accuracy of 82.22% within the tolerance range of ±50 ms. © 2020, Springer Nature Switzerland AG.
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.