Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/7600,
  title    = {Multi Switched Split Vector Quantization of Narrowband Speech Signals},
  author    = {M. Satya Sai Ram and  P. Siddaiah and  M. Madhavi Latha},
  country   = {},
  institution={},
  abstract  = {Vector quantization is a powerful tool for speech
coding applications. This paper deals with LPC Coding of speech
signals which uses a new technique called Multi Switched Split
Vector Quantization (MSSVQ), which is a hybrid of Multi, switched,
split vector quantization techniques. The spectral distortion
performance, computational complexity, and memory requirements
of MSSVQ are compared to split vector quantization (SVQ), multi
stage vector quantization(MSVQ) and switched split vector
quantization (SSVQ) techniques. It has been proved from results that
MSSVQ has better spectral distortion performance, lower
computational complexity and lower memory requirements when
compared to all the above mentioned product code vector
quantization techniques. Computational complexity is measured in
floating point operations (flops), and memory requirements is
measured in (floats).},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {2},
  number    = {1},
  year      = {2008},
  pages     = {35 - 38},
  ee        = {http://waset.org/publications/7600},
  url       = {http://waset.org/Publications?p=13},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 13, 2008},
}