A Speaker Identification System Using MFCC Features with VQ Technique
IITA '09 Proceedings of the 2009 Third International Symposium on Intelligent Information Technology Application - Volume 03
Image retrieval using DCT on row mean, column mean and both with image fragmentation
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
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In this paper a simple approach to text dependent speaker identification using spectrograms and row mean is presented. This, mainly, revolves around trapping the complex patterns of variation in frequency and amplitude with time while an individual utters a given word through equalized spectrogram. These equalized spectrograms are used as a database to successfully identify the unknown individual from his/her voice. The features used for identifying, rely on optimal spectrogram segmentation and the Euclidean distance of the distributional features of the spectrograms of the unknown voice with that of a given known speaker in the database. Performance of this novel approach on a sample collected as two separate databases from 12 speakers and 28 speakers show that this methodology can be effectively used to produce a desirable success rate.