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Linear versus Mel Frequency Cepstral Coefficients for Speaker Recognition (Author's Manuscript)

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University of Maryland College Park United States

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Mel-frequency cepstral coefficients MFCC have been dominantly used in speaker recognition as well as in speech recognition. However, based on theories in speech production, some speaker characteristics associated with the structure of the vocal tract, particularly the vocal tract length, are reflected more in the high frequency range of speech. This insight suggests that a linear scale in frequency may provide some advantages in speaker recognition over the mel scale. Based on two state-of-the-art speaker recognition back-end systems one Joint Factor Analysis system and one Probabilistic Linear Discriminant Analysis system, this study compares the performances between MFCC and LFCC Linear frequency cepstral coefficients in the NIST SRE Speaker Recognition Evaluation 2010 extended-core task. Our results in SRE10 show that, while they are complementary to each other, LFCC consistently outperforms MFCC, mainly due to its better performance in the female trials. This can be explained by the relatively shorter vocal tract in females and the resulting higher formant frequencies in speech. LFCC benefits more in female speech by better capturing the spectral characteristics in the high frequency region. In addition, our results show some advantage of LFCC over MFCC in reverberant speech. LFCC is as robust as MFCC in the babble noise, but not in the white noise. It is concluded that LFCC should be more widely used, at least for the female trials, by the mainstream of the speaker recognition community.

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Conference Paper

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2011 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) , 11 Dec 2011, 15 Dec 2011,



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Approved For Public Release;

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