Fast Speaker Identification using Recursive Word Sample Attributes

idth and Formants Ratio. At first, the PRAA database is trained by these methods, this method has used five clustered for bandwidth and also formants ratio. These clusters are classified on the behalf of fuzzy members, and thereafter each and every cluster of bandwidth and formants ratio are combined in different type of combinations. In the testing section, voice samples taken from speakers are compared with these combinations. These systems make them provided fast voice identification process. The Experiment result of the proposed work is achieved more than 98% of Identification Rate.