Name
Abstract | ||
|---|---|---|
This paper presents an original speaker recognition system that utilizes a quantized spectral covariance matrix on the input to a two-dimensional Principal Component Analysis (2DPCA) function. Eigenvoice algorithm is used as a classifying tool and is generated by the features of a group of speakers. The proposed system is selective in acquiring acoustic parameters and leads to a significant decrease in storage requirements. The system is robust in a noisy environment with recognition rates as high as 92% at 0dB SNR. Concatenated vowels that make up the speech signal are extracted from the TIMIT database and the noise environment is acquired from the NOIZEOUS database. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/MWSCAS.2013.6674848 | Midwest Symposium on Circuits and Systems Conference Proceedings |
Keywords | Field | DocType |
Hamming window,2D-FFT,2D-PCA,Eigenvectors,Covariance matrix | Eigenface,Pattern recognition,Computer science,Speech recognition,Speaker recognition system,Timit database,Speaker recognition,Concatenation,Artificial intelligence,Covariance matrix,Principal component analysis | Conference |
ISSN | Citations | PageRank |
1548-3746 | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| genevieve i sapijaszko | 1 | 0 | 0.68 |
| Wasfy B. Mikhael | 2 | 76 | 76.27 |