Title
A Combined Approach to Text-Dependent Speaker Identification: Comparison with Pure Neural Net Approaches
Abstract
A novel approach to automatic speaker identification (ASI) is presented. Most of the present automatic speaker identification systems based on neural networks have no definite mechanisms to compensate for time distortions due to elocution. Such models have less precise information about the intraspeaker measure. The new combined approach uses both distortion-based and discriminant-based methods. The distortion-based and discriminant-based methods are dynamic time warping (DTW) and artificial neural network (ANN) respectively. This paper compares this new classifier with a pure neural net classifier for speaker identification. The performance of the combined classifier surpasses that of a pure ANN classifier for the conditions tested.
Year
DOI
Venue
1998
10.1142/S0218126698000110
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
Keywords
DocType
Volume
artificial neural network,neural network,artificial intelligent,dynamic time warping,neural net
Journal
8
Issue
ISSN
Citations 
2
0218-1266
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Qianhui Liang127520.24
Miaoliang Zhu2154.22