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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Verma, G.K. Tiwary, U.S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Indian Institute of Information Technology Allahabad, Jhalwa, Allahabad, India - 211 012 (Verma, G.K.; Tiwary, U.S.) |
| Abstract | The purpose of this paper is to evolve a robust text independent speaker identification system based on the wavelet transform, which is able to analyze signal at multiple resolutions. The proposed system identifies speakers by their acoustic characteristics embedded in speech signal of speakers. Features are obtained from approximation and detail coefficients by calculating entropy, standard deviation and mean at each decomposition level. The similarity between the extracted features and a set of reference features is calculated by means of K-NN classifier to determine the speaker's identity. The results are evaluated with VoxForge speech corpus containing more than 200 speakers and each speaker profile contains ten speech signals. The results achieved are promising with 83.9 % accuracy for 200 speakers. Some popular existing methods are also evaluated for comparison in this paper. The result shows that the proposed method is more effective and robust than other methods. The performance of our system is very good with noisy dataset at different SNR. |
| Starting Page | 130 |
| Ending Page | 134 |
| File Size | 493737 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424490332 |
| e-ISBN | 9781424490349 |
| DOI | 10.1109/ICCCT.2010.5640426 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-17 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Discrete Wavelet Transform (DWT) K-Nearest Neighbor (KNN) Classifier Speech Feature extraction Wavelet analysis Speaker Identification System Discrete wavelet transforms Noise measurement |
| Content Type | Text |
| Resource Type | Article |
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