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Speech Coding Based on Spectral Dynamics

  • Petr Motlíček
  • Hynek Hermansky
  • Harinath Garudadri
  • Naveen Srinivasamurthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4188)

Abstract

In this paper we present first experimental results with a novel audio coding technique based on approximating Hilbert envelopes of relatively long segments of audio signal in critical-band-sized sub-bands by autoregressive model. We exploit the generalized autocorrelation linear predictive technique that allows for a better control of fitting the peaks and troughs of the envelope in the sub-band. Despite introducing longer algorithmic delay, improved coding efficiency is achieved. Since the described technique does not directly model short-term spectral envelopes of the signal, it is suitable not only for coding speech but also for coding of other audio signals.

Keywords

Discrete Cosine Transform Audio Signal Linear Prediction Vocal Tract Inverse Discrete Cosine Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Petr Motlíček
    • 1
    • 2
  • Hynek Hermansky
    • 1
    • 2
    • 3
  • Harinath Garudadri
    • 4
  • Naveen Srinivasamurthy
    • 4
  1. 1.IDIAP Research InstituteMartignySwitzerland
  2. 2.Faculty of Information TechnologyBrno University of TechnologyBrnoCzech Republic
  3. 3.École Polytechnique Fédérale de Lausanne (EPFL)Switzerland
  4. 4.Qualcomm Inc.San DiegoUSA

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