Name
Title | ||
|---|---|---|
A performance evaluation study of four wavelet algorithms for the pitch period estimation of speech signals |
Abstract | ||
|---|---|---|
Pitch period is considered an important parameter in designing an automatic speaker recognition/identification system. Recently, inspired by application of multiscale analysis to edge detection in image processing, a new technique for pitch detection and estimation, based on the dyadic wavelet transform, was developed. In this paper we provide a more general setting for the wavelet based pitch estimation methodology: we show that certain restrictions on the window function, inherent in wavelet analysis, are unnecessary, and that discretization of the dilation parameter on a finer than the dyadic scale Can be used advantageously in the multiscale pitch detection scheme. (C) 1998 Elsevier Science Inc. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1016/S0020-0255(98)10032-4 | Inf. Sci. |
Keywords | Field | DocType |
wavelet algorithm,speech signal,pitch period estimation,performance evaluation study,speech processing,wavelet transform,edge detection,image processing,wavelet analysis | Pattern recognition,Lifting scheme,Computer science,Algorithm,Second-generation wavelet transform,Discrete wavelet transform,Artificial intelligence,Stationary wavelet transform,Wavelet packet decomposition,Pitch detection algorithm,Wavelet,Wavelet transform | Journal |
Volume | Issue | ISSN |
112 | 1-4 | 0020-0255 |
Citations | PageRank | References |
4 | 0.61 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad S. Obaidat | 1 | 2190 | 315.70 |
| Andy Brodzik | 2 | 4 | 0.61 |
| B. Sadoun | 3 | 138 | 12.08 |