Vector quantization of speech frames based on self-organizing maps.

@article{Simes2010VectorQO,
  title={Vector quantization of speech frames based on self-organizing maps.},
  author={Fl{\'a}vio Olmos Sim{\~o}es and Mario Uliani Neto and Jeremias Barbosa Machado and Edson Jose Nagle and Fernando Oscar Runstein and Leandro de Campos Teixeira Gomes},
  journal={Advances in experimental medicine and biology},
  year={2010},
  volume={657},
  pages={
          201-16
        }
}
We propose a speech compression technique based on vector quantization. A neural network with unsupervised learning is used to implement the vector quantizer. Some basic aspects related to speech signal processing are presented, as well as some general issues concerning the vector quantization problem. The idea of using a codebook to perform speech compression is introduced, and the use of a 2-dimensional self-organizing Kohonen map to generate the codebook is proposed. Simulation results are… CONTINUE READING
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