• 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
  • Spectral estimation using higher-lag autocorrelation coefficients with applications to speech recognition

    Thumbnail
    View/Open
    32206.pdf (527.9Kb)
    Author(s)
    Shannon, BJ
    Paliwal, KK
    Griffith University Author(s)
    Paliwal, Kuldip K.
    Year published
    2005
    Metadata
    Show full item record
    Abstract
    In this paper, we introduce a noise robust spectral estimation technique for speech signals that is derived from a windowed one-sided higher-lag autocorrelation sequence. We also introduce a new high dynamic range window design method, and utilise both techniques in a modi ed Mel Frequency Cepstral Coef cient (MFCC) algorithm to produce noise robust speech recognition features. We call the new features Autocorrelation Mel Frequency Cepstral Coef cients (AMFCCs). We compare the recognition performance of AMFCCs to MFCCs for a range of stationary and non-stationary noises on the Aurora II database. We show that the AMFCC ...
    View more >
    In this paper, we introduce a noise robust spectral estimation technique for speech signals that is derived from a windowed one-sided higher-lag autocorrelation sequence. We also introduce a new high dynamic range window design method, and utilise both techniques in a modi ed Mel Frequency Cepstral Coef cient (MFCC) algorithm to produce noise robust speech recognition features. We call the new features Autocorrelation Mel Frequency Cepstral Coef cients (AMFCCs). We compare the recognition performance of AMFCCs to MFCCs for a range of stationary and non-stationary noises on the Aurora II database. We show that the AMFCC features perform as well as MFCCs in clean conditions and have higher noise robustness in noisy conditions.
    View less >
    Conference Title
    ISSPA 2005: The 8th International Symposium on Signal Processing and its Applications, Vols 1 and 2, Proceedings
    Volume
    2
    DOI
    https://doi.org/10.1109/ISSPA.2005.1581009
    Copyright Statement
    © 2005 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.
    Publication URI
    http://hdl.handle.net/10072/2576
    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