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Related Experiment Videos

2-D-CELP image coding with block-adaptive prediction and variable code-vector size.

S Aissa1, E Dubois

  • 1Dept. of Electr. Eng., McGill Univ., Montreal, Que.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1996
PubMed
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A new block-oriented method designs linear predictors using clustering for speech coding. This approach improves switched prediction in 2-D code excited linear prediction (2-D-CELP) systems, especially with variable block sizes.

Area of Science:

  • Digital Signal Processing
  • Speech Compression
  • Machine Learning

Background:

  • Linear predictive coding is fundamental to speech compression.
  • Switched prediction enhances coding efficiency by adapting predictor selection.
  • Existing methods may not fully exploit data variability.

Purpose of the Study:

  • To introduce a novel block-oriented method for designing finite sets of linear predictors.
  • To evaluate the performance of these predictors in DPCM and 2-D-CELP systems.
  • To propose an enhanced 2-D-CELP system utilizing variable block sizes.

Main Methods:

  • A clustering algorithm is applied to a training set to generate a finite set of linear predictors.
  • The designed predictors are integrated into switched prediction frameworks for DPCM and 2-D-CELP.

Related Experiment Videos

  • A variable block size (VB 2-D-CELP) approach is developed.

    • Main Results:

    • The block-oriented predictor design method demonstrates effectiveness.
    • Integration with switched prediction yields performance improvements.
    • The proposed VB 2-D-CELP system shows enhanced coding capabilities.

    Conclusions:

    • The proposed block-oriented predictor design is a viable approach for speech coding.
    • Switched prediction combined with adaptive block sizes offers significant advantages.
    • The developed VB 2-D-CELP system represents an advancement in speech compression technology.