Mr. Mohammed Imdad N, Prof. Shameem Akhtar N, Prof.Mohammad Imran Akhtar


This paper investigates the problem of speaker identification and verification in noisy conditions, assuming that speech signals are corrupted by noise. This paper describes a method that combines multi-condition model training and missing-feature theory to model noise with unknown temporal-spectral characteristics. Introduction of such technique is very useful since it remove avoids the problem of recognizing voice and can also be implemented since here user is not required to remember his password login and hence no stilling chance.


Cepstrum, Missing Feature method, Multi-condition model training, Vector quantization


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