Wavelet-based Adaptive Multiresolution Tools Applied to Speech Recognition

  • * naive examples which show drawbacks of discrete wavelet transform and windowed Fourier transform; * adaptive partition (with a 'best basis' approach) of speech-like signals by means of local trigonometric bases with orthonormal windows. * extraction of formant-like features from the cosine transform; * further proceedingings for classification of vowels or voiced speech are suggested at the end.

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Metadaten
Author:Andreas Simon
URN:urn:nbn:de:hbz:386-kluedo-14503
Document Type:Diploma Thesis
Language of publication:English
Year of Completion:2006
Year of first Publication:2006
Publishing Institution:Technische Universität Kaiserslautern
Granting Institution:Technische Universität Kaiserslautern
Date of the Publication (Server):2006/10/17
Tag:best basis; biorthogonal bases of L^2; entropy; formants; local trigonometric packets; spectrogram; speech recognition; wavelet packets; wavelets
Faculties / Organisational entities:Kaiserslautern - Fachbereich Mathematik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 510 Mathematik
Licence (German):Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011