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Multi-feature Fusion for Closed Set Text Independent Speaker Identification

  • Conference paper
Information Intelligence, Systems, Technology and Management (ICISTM 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 141))

Abstract

An intra-modal fusion, a fusion of different features of the same modal is proposed for speaker identification system. Two fusion methods at feature level and at decision level for multiple features are proposed in this study. We used multiple features from MFCC and wavelet transform of speech signal. Wavelet transform based features capture frequency variation across time while MFCC features mainly approximate the base frequency information, and both are important. A final score is calculated using weighted sum rule by taking matching results of different features. We evaluate the proposed fusion strategies on VoxForge speech dataset using K-Nearest Neighbor classifier. We got the promising result with multiple features in compare to separate one. Further, multi-features also performed well at different SNRs on NOIZEUS, a noisy speech corpus.

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Author information

Authors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, Jhalwa, Allahabad, India

    Gyanendra K. Verma

Authors
  1. Gyanendra K. Verma
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Editor information

Editors and Affiliations

  1. Computer Science, College of Engineering and Science, Louisiana Tech University, 71272, Ruston, LA, USA

    Sumeet Dua

  2. CISE Department, CSE 301, University of Florida, 32611, Gainesville, FL, USA

    Sartaj Sahni

  3. Management Development Institute, 122 007, Sukhrali, Gurgaon, India

    D. P. Goyal

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© 2011 Springer-Verlag Berlin Heidelberg

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Verma, G.K. (2011). Multi-feature Fusion for Closed Set Text Independent Speaker Identification. In: Dua, S., Sahni, S., Goyal, D.P. (eds) Information Intelligence, Systems, Technology and Management. ICISTM 2011. Communications in Computer and Information Science, vol 141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19423-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-19423-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19422-1

  • Online ISBN: 978-3-642-19423-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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