Learning Speech as Acoustic Sequences with the Unsupervised Model , TOM

@inproceedings{Durand1995LearningSA,
  title={Learning Speech as Acoustic Sequences with the Unsupervised Model , TOM},
  author={St{\'e}phane Durand and Fr{\'e}d{\'e}ric Alexandre},
  year={1995}
}
Most connectionist systems do not involve the temporal dimension. However, some neural networks attempt to take time into account either inside or outside the network. Speech recognition is a stochastic problem that involves a dynamic parameter. The recognitionof a unit of speech depends on the contextual information i.e., the parts around it. Our approach consists of interpreting the speech signal as a sequence of acoustic informationand designing a neural network, called TOM or Temporal… CONTINUE READING
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