Cepstral domain segmental nonlinear feature transformations for robust speech recognition

@article{Segura2004CepstralDS,
  title={Cepstral domain segmental nonlinear feature transformations for robust speech recognition},
  author={Jos{\'e} C. Segura and M. Carmen Ben{\'i}tez and {\'A}ngel de la Torre and Antonio J. Rubio and Javier Ram{\'i}rez},
  journal={IEEE Signal Processing Letters},
  year={2004},
  volume={11},
  pages={517-520}
}
This letter presents a new segmental nonlinear feature normalization algorithm to improve the robustness of speech recognition systems against variations of the acoustic environment. An experimental study of the best delay-performance tradeoff is conducted within the AURORA-2 framework, and a comparison with two commonly used normalization algorithms is presented. Computationally efficient algorithms based on order statistics are also presented. One of them is based on linear interpolation… CONTINUE READING
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