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A scalable speech coding scheme using compressive sensing and orthogonal mapping based vector quantization.

M S Arun Sankar1, P S Sathidevi1

  • 1Department of Electronics and Communication Engineering, National Institute of Technology Calicut, Kerala, India.

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Summary
This summary is machine-generated.

This study introduces a novel scalable speech coding scheme using Compressive Sensing (CS). The new method offers combined compression, encryption, and de-noising, achieving quality comparable to existing codecs at various bit rates.

Keywords:
CELPCompressive sensingElectrical engineeringSpeech codingSpeech compressionSpeech processingWavelet

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Area of Science:

  • Digital Signal Processing
  • Information Theory
  • Speech Communication

Background:

  • Speech coding is crucial for efficient transmission and storage.
  • Existing methods face challenges with non-stationary signals and complexity.
  • Compressive Sensing (CS) offers potential for combined compression and de-noising.

Purpose of the Study:

  • To design and implement a novel scalable speech coding scheme using Compressive Sensing (CS).
  • To reduce the complexity of the CS recovery process for non-stationary speech signals.
  • To improve the performance and coding efficiency of CS-based speech coding.

Main Methods:

  • Developed a CS-based speech coding scheme operating at 3.275–7.275 kbps.
  • Reduced recovery complexity by assigning adaptive sparsifying bases per speech frame.
  • Proposed a Binary Permuted Block Diagonal (BPBD) sensing matrix for improved performance.
  • Utilized Vector Quantization (VQ) and orthogonal mapping VQ for efficient quantization.

Main Results:

  • Achieved listening quality comparable to Adaptive Multi rate-Narrowband (AMR-NB) and Enhanced Voice Services (EVS) codecs.
  • Demonstrated inherent de-noising capabilities, eliminating the need for a separate de-noising block.
  • Showcased bit rate scalability by adjusting measurement numbers and VQ levels.

Conclusions:

  • The proposed CS-based speech coding scheme offers a scalable, efficient, and high-quality solution.
  • Adaptive basis selection and improved sensing matrices enhance CS performance for speech.
  • The inherent de-noising and combined compression/encryption features provide significant advantages.