Combining evidence from spectral and source-like features for person recognition from humming

Hemant A. Patil, Maulik C. Madhavi, Keshab K. Parhi

Research output: Contribution to journalConference article

8 Scopus citations

Abstract

In this paper, hum of a person is used in voice biometric system. In addition, recently proposed feature set, i.e., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC), is found to capture perceptually meaningful source-like information from hum signal. For person recognition, MFCC gives EER of 13.14% and %ID of 64.96%. A reduction in equal error rate (EER) by 0.2% and improvement in identification rate by 7.3 % is achieved when a score-level fusion system is employed by combining evidence from MFCC (system) and VTMFCC (source-like features) than MFCC alone. Results are reported for various feature dimensions and population sizes.

Original languageEnglish (US)
Pages (from-to)369-372
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - Dec 1 2011
Event12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
Duration: Aug 27 2011Aug 31 2011

Keywords

  • Fusion of Source-System features
  • Humming
  • Polynomial classifier
  • VTEO
  • VTMFCC

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