A New Set of Features for Text-Independent Speaker Identification

被引：0
|
作者：
Espy-Wilson, Carol Y. [1 ]
Manocha, Sandeep
Vishnubhotla, Srikanth
机构：
[1] Univ Maryland, Syst Res Inst, College Pk, MD 20742 USA
来源：
INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, VOLS 1-5 | 2006年
关键词：
speaker identification; acoustic parameters; Gaussian Mixture Models (GMM); Mel-Frequency Cepstral Coefficients (MFCC); speaker specific features;
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：
The success of a speaker identification system depends largely on the set of features used to characterize speaker-specific information. In this paper, we discuss a small set of low-level acoustic parameters that capture information about the speaker's source, vocal tract size and vocal tract shape. We demonstrate that the set of eight acoustic parameters has comparable performance to the standard sets of 26 or 39 MFCCs for the speaker identification task. Gaussian Mixture Models were used for constructing speaker models.
引用
收藏
页码：1475 / +
页数：2
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