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文章基本信息

  • 标题:Very Low Rate Scalable Speech Coding through Classified Embedded Matrix Quantization
  • 本地全文:下载
  • 作者:Ehsan Jahangiri ; Shahrokh Ghaemmaghami
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2010
  • 卷号:2010
  • DOI:10.1155/2010/480345
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the LSFs in the LPC model. For an efficient quantization of the spectral parameters, two types of codebooks of different sizes are designed and used to encode unvoiced and mixed voicing segments separately. The tree-like structured codebooks of our embedded quantizer, constructed through a cell merging process, help to make a fine-grain scalable speech coder. Using an efficient adaptive dual-band approximation of the LPC excitation, where voicing transition frequency is determined based on the concept of instantaneous frequency in the frequency domain, near natural sounding synthesized speech is achieved. Assessment results, including both overall quality and intelligibility scores show that the proposed coding scheme can be a reasonable choice for speech coding in low bandwidth communication applications.

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