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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| 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 |