A New Strategy of Direct Access for Speaker Identification System Based on Classification
Abstract: In this paper, we
present a new direct access strategy for speaker identification system. DAMClass
is a method for direct access strategy that speeds up the identification
process without decreasing the identification rate drastically. This proposed
method uses speaker classification strategy based on human voice’s original
characteristics, such as pitch, flatness, brightness, and roll off. DAMClass decomposes
available dataset into smaller sub-datasets in the form of classes or buckets
based on the similarity of speaker’s original characteristics. DAMClass builds
speaker dataset index based on range-based indexing of direct access facility
and uses nearest neighbor search, range-based searching and multiclass-SVM
mapping as its access method. Experiments show that the direct access strategy
with multiclass-SVM algorithm outperforms the indexing accuracy of range-based
indexing and nearest neighbor for one to nine percent. DAMClass is shown to
speed up the identification process 16 times faster than sequential access
method with 91.05% indexing accuracy.
Author: Hery Heryanto, Saiful
Akbar, Benhard Sitohang
Journal Code: jptkomputergg150161
