Fine granularity scalable speech coding using embedded tree-structured vector quantization

  • Authors:
  • Mouloud Djamah;Douglas O'Shaughnessy

  • Affiliations:
  • INRS-EMT, University of Quebec, Montreal, Canada;INRS-EMT, University of Quebec, Montreal, Canada

  • Venue:
  • Speech Communication
  • Year:
  • 2012

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Abstract

This paper proposes an efficient codebook design for tree-structured vector quantization (TSVQ) that is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and/or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech. A fast search encoding algorithm using multistage tree-structured vector quantization (MTVQ) is proposed for quantization of LSF's. The proposed method is compared to the multipath sequential tree-assisted search (MSTS) and to the well known multipath sequential search (MSS) or M-L search algorithms.