Exemplar-Based Processing for Speech Recognition: An Overview

@article{Sainath2012ExemplarBasedPF,
  title={Exemplar-Based Processing for Speech Recognition: An Overview},
  author={Tara N. Sainath and Bhuvana Ramabhadran and David Nahamoo and Dimitri Kanevsky and Dirk Van Compernolle and Kris Demuynck and Jort F. Gemmeke and Jerome R. Bellegarda and Shiva Sundaram},
  journal={IEEE Signal Processing Magazine},
  year={2012},
  volume={29},
  pages={98-113}
}
Solving real-world classification and recognition problems requires a principled way of modeling the physical phenomena generating the observed data and the uncertainty in it. The uncertainty originates from the fact that many data generation aspects are influenced by nondirectly measurable variables or are too complex to model and hence are treated as random fluctuations. For example, in speech production, uncertainty could arise from vocal tract variations among different people or corruption… CONTINUE READING

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Data selection for noise robust exemplar matching

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