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Intelligent Classification Systems

  • Andrey V. Savchenko
Chapter
Part of the SpringerBriefs in Optimization book series (BRIEFSOPTI)

Abstract

The design of intelligent classifications systems is a very broad research topic, that covers a large number of individual tasks, e.g., data preprocessing, feature extraction, segmentation, learning of classifier, etc. One of the most challenging problems is the recognition of the audiovisual data, such as speech signals, complex images, etc. A brief review of the known classification methods is given, and these methods are systematized in accordance to the number of available reference instances and the number of classes in the database. The comparison of the classifiers in terms of the multi-criteria optimization is studied. Namely, we take into account not only the classification accuracy, but also the runtime complexity of the algorithm. Moreover, the need for exploration of the system behavior in the presence of artificially generated noise is highlighted.

Keywords

Support Vector Machine Speech Signal Gaussian Mixture Model Near Neighbor Automatic Speech Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2016

Authors and Affiliations

  • Andrey V. Savchenko
    • 1
  1. 1.Laboratory of Algorithms and Technologies for Network AnalysisNational Research University Higher School of EconomicsNizhny NovgorodRussia

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