Combining Evidence from Spectral and Source-like Features for Person Recognition from Humming

被引：0
|
作者：
Patil, Hemant A. [1 ]
Madhavi, Maulik C. [1 ]
Parhi, Keshab K. [2 ]
机构：
[1] Dhirubhai Ambani Inst Informat & Commun Technol, Gandhiangar, India
[2] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN USA
来源：
12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | 2011年
关键词：
Humming; VTEO; VTMFCC; fusion of Source-System features; polynomial classifier; SPEAKER RECOGNITION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, hum of a person is used in voice biometric system. In addition, recently proposed feature set, i.e., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC), is found to capture perceptually meaningful source-like information from hum signal. For person recognition, MFCC gives EER of 13.14% and %ID of 64.96%. A reduction in equal error rate (EER) by 0.2% and improvement in identification rate by 7.3 % is achieved when a score-level fusion system is employed by combining evidence from MFCC (system) and VTMFCC (source-like features) than MFCC alone. Results are reported for various feature dimensions and population sizes.
引用
收藏
页码：376 / +
页数：2
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