NDLI: Novel Variable length Teager Energy Based features for person recognition from their hum

Content Provider	IEEE Xplore Digital Library
Author	Patil, Hemant A. Parhi, Keshab K.
Copyright Year	2010
Description	Author affiliation: Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, India-382 007 (Patil, Hemant A.) \|\| Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, 55455, USA (Parhi, Keshab K.)
Abstract	Most of the state-of-the-art voice biometrics systems use the natural speech signal (either read speech or spontaneous or contextual speech) from the subjects. In this paper, an attempt is made to identify speakers from their hum. A new feature set, viz., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC) is proposed for this problem. Experiments have been carried out for person identification and verification task using Linear Prediction Cepstral Coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC) with polynomial classifier of $2^{nd}$ order approximation. It is shown that the speaker identification rate for proposed feature set outperforms LPCC by 13.6% and is competitive over baseline MFCC. For speaker verification, a reduction in equal error rate (EER) by 1.73% is achieved when a score-level fusion system is employed by combining evidence from MFCC and VTMFCC.
Starting Page	4526
Ending Page	4529
File Size	257598
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mel frequency cepstral coefficient Speech Speech processing Biometrics Polynomials Speaker recognition Spectrogram VTEO Voice biometrics Humming
Content Type	Text
Resource Type	Article

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