Combining Dynamic Features with MFCC for Text-independent Speaker Identification

被引：0
|
作者：
Chaudhari, Amol [1 ]
Rahulkar, Amol [2 ]
Dhonde, S. B. [1 ]
机构：
[1] AISSMS Inst Informat Technol, Dept Elect Engn, Pune, Maharashtra, India
[2] Natl Inst Technol Goa, Dept Elect & Elect Engn, Ponda, India
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING (ICIP) | 2015年
关键词：
Cepstral Coefficients; Mel frequency cepstrut coefficients; LBG algorithm; Euclidean distance; MULTITAPER MFCC; VERIFICATION; RECOGNITION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents text-independent speaker identification scheme based on the combination of dynamic features with Mel Frequency Cepstral Coefficients (MFCC). First, MFCCs are used to extract the speaker specific features and then vector quantization is used to model the speaker. We compare the performance of speaker identification system using number of MFCC filters and centroids of vector quantization. In addition, we also compare the effect of possible combinations of MFCC with log energy, delta and double delta coefficients for number of filters and centroids of vector quantization on recognition rate. The experimental results have been evaluated on the developed database of 75 speakers.
引用
收藏
页码：160 / 164
页数：5
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