Name
Abstract | ||
|---|---|---|
This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1142/S0219691310003894 | INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING |
Keywords | DocType | Volume |
Speaker verification, discrete wavelet transform, FIR filters | Journal | 8 |
Issue | ISSN | Citations |
6 | 0219-6913 | 1 |
PageRank | References | Authors |
0.39 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michel Alves Lacerda | 1 | 1 | 0.73 |
| Rodrigo Capobianco Guido | 2 | 161 | 27.59 |
| Leonardo Mendes de Souza | 3 | 1 | 0.39 |
| Paulo Ricardo Franchi Zulato | 4 | 1 | 0.73 |
| Jussara Ribeiro | 5 | 1 | 0.73 |
| Shi-Huang Chen | 6 | 1 | 0.39 |