| Author(s) | Rabah W. Aldhaheri* and Fuad E. Al-Saadi** |
| Affiliation | *Department of Electrical and Computer Engineering, King Abdulaziz University, P.O.Box 80204, Jeddah 21589, Saudi Arabia **Department of Communication, Jeddah College of Electronics and Communication, P.O.Box 16947, Jeddah 21474, Saudi Arabia |
| Title | Robust Text-independent Speaker Recognition with Short Utterance in Noisy Environment Using SVD as a Matching Measure |
| Source | Journal of King Saud University. Computer & Information Sciences. Volume 17, No 1. (2005/1425) |
| Abstract | A new technique for text-independent speaker recognition for noisy speech is presented. This technique is based on finding the ratio of the singular values of the feature vectors of the unknown speaker and each of the N reference features stored in the constructed database. The reference feature that gives the largest ratio is considered the feature of the unknown speaker. An overall correct recognition accuracy of 94% for clean speech and 32% for noisy speech of 0 dB SNR was obtained. A further step was conducted to enhance the noisy features by series expansion. The improvement in the recognition rate using the proposed SVD-based algorithm is compared with other distance measure algorithms. It is found that the proposed technique when cepstral features are used outperforms the conventional matching measure such as the Euclidean, the Weighted and the Mahalonobis distances, respectively. |
