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ICASSP
2010
IEEE

Robust speaker identification using an auditory-based feature

13 years 11 months ago
Robust speaker identification using an auditory-based feature
An auditory-based feature extraction algorithm is presented. The feature is based on a recently published time-frequency transform plus a set of modules to simulate the signal processing functions in the cochlea. The feature is applied to a speaker identi cation task to address the acoustic mismatch problem between training and testing. Usually, the performances of acoustic models trained in clean speech drop signi cantly when tested on noisy speech. The proposed feature has shown strong robustness in the mismatched situation. As shown in our experiments, in a speaker identi cation task, both MFCC and the proposed feature have near perfect performances in a clean testing condition, but when the SNR of input signal drops to 6
Qi Li, Yan Huang
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICASSP
Authors Qi Li, Yan Huang
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