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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mahmood, A. Alsulaiman, M. Muhammad, G. |
| Copyright Year | 2012 |
| Abstract | This paper proposes a new feature extraction method called multi-directional local feature (MDLF) to apply on an automatic speaker recognition system. To obtain MDLF, a linear regression is applied on FFT signal in four different directions which are horizontal (time axis), vertical (frequency axis), diagonal 45 degree (time-frequency) and diagonal 135 degree (time-frequency). In the experiments, Gaussian mixture model with different number of mixtures is used as classifier. Different experiments were conducted using all alphabets of Arabic for speaker recognition systems. Experimental results show that the proposed MDLF achieves better recognition accuracies than the traditional MFCC and Local features for speaker recognition system. |
| Starting Page | 308 |
| Ending Page | 311 |
| File Size | 269293 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467308861 |
| DOI | 10.1109/ISMS.2012.45 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-02-08 |
| Publisher Place | Malaysia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Accuracy GMM Feature extraction Time frequency analysis Speech Local feature Arabic speaker recognition Speaker recognition Mel frequency cepstral coefficient MFCC Multidirectional local feature (MDLF) |
| Content Type | Text |
| Resource Type | Article |
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