Szczegóły publikacji
Opis bibliograficzny
Wavelet speech feature extraction using mean best basis algorithm / Jakub GAŁKA, Mariusz ZIÓŁKO // W: Advances in nonlinear speech processing : international conference on Nonlinear speech processing, NOLISP 2009 : Vic, Spain, June 25–27, 2009 : revised selected papers / eds. Jordi Solé-Casals, Vladimir Zaiats. — Berlin ; Heidelberg : Springer-Verlag, 2010. — ( Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 5933. Lecture Notes in Artificial Intelligence ). — ISBN: 978-3-642-11508-0; ISBN: 3-642-11508-X. — S. 128–135. — Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 51774 |
|---|---|
| Data dodania do BaDAP | 2010-05-14 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-642-11509-7_17 |
| Rok publikacji | 2010 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
This paper presents Mean Best Basis algorithm, an extension of the well known Best Basis Wickerhouser’s method, for an adaptive wavelet decomposition of variable-length signals. A novel approach is used to obtain a decomposition tree of the wavelet-packet cosine hybrid transform for speech signal feature extraction. Obtained features are tested using the Polish language hidden Markov model phone classifier.
