• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    • Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Using long-term information to improve robustness in speaker identification

    Thumbnail
    View/Open
    68644_1.pdf (127.3Kb)
    Author(s)
    Lyons, James G
    O'Connell, James G
    Paliwal, Kuldip K
    Griffith University Author(s)
    Paliwal, Kuldip K.
    Year published
    2010
    Metadata
    Show full item record
    Abstract
    In this paper we propose two new methods of improving the robustness of Automatic Speaker Identification systems. These methods rely on using long-term information in the speech signal to improve the robustness of the features. The first method involves averaging filterbank parameters from consecutive short-time frames over a longer window. The second method investigates the use of frame lengths longer than generally assumed stationary. We show that these two methods result in an improvement over standard Mel Frequency Cepstral Coefficients in the presence of additive white Gaussian noise in speaker identification applications. ...
    View more >
    In this paper we propose two new methods of improving the robustness of Automatic Speaker Identification systems. These methods rely on using long-term information in the speech signal to improve the robustness of the features. The first method involves averaging filterbank parameters from consecutive short-time frames over a longer window. The second method investigates the use of frame lengths longer than generally assumed stationary. We show that these two methods result in an improvement over standard Mel Frequency Cepstral Coefficients in the presence of additive white Gaussian noise in speaker identification applications. Furthermore, additional improvements are observed at mid-range SNR when the proposed methods are used in combination.
    View less >
    Conference Title
    2010 4TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS)
    DOI
    https://doi.org/10.1109/ICSPCS.2010.5709772
    Copyright Statement
    © 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Subject
    Signal processing
    Publication URI
    http://hdl.handle.net/10072/37259
    Collection
    • Conference outputs

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E
    • TEQSA: PRV12076

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander