Fractional Fourier Transform Based Auditory Feature for Language Identification

被引：5

作者：

Zhang, Wei-Qiang ^{[1
]}

He, Liang ^{[1
]}

Hou, Tao ^{[1
]}

Liu, Jia ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China

来源：

2008 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (APCCAS 2008), VOLS 1-4 | 2008年

关键词：

D O I：

10.1109/APCCAS.2008.4745997

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a novel auditory feature based on fractional Fourier transform (FRET), namely, fractional auditory cepstrum coefficient (FACC), is presented for language identification (LID). Different from the widely used Mel-frequency cepstrum coefficient (MFCC), the proposed feature utilizes the human auditory model and performs Gammatone filtering for the short-time fractional spectrum of the speech. Experimental results on NIST 2003 Language Recognition Evaluation (LRE03) show that the FACC feature decreases the equal error rate (EER) of 10.5% relatively when compared with the MFCC feature.

引用

页码：209 / 212

页数：4

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