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Constructing Empirical Models for Automatic Dialog Parameterization

  • Mikhail Alexandrov
  • Xavier Blanco
  • Natalia Ponomareva
  • Paolo Rosso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4629)

Abstract

Automatic classification of dialogues between clients and a ser vice center needs a preliminary dialogue parameterization. Such a pa rameterization is usually faced with essential difficulties when we deal with politeness, competence, satisfaction, and other similar characteris tics of clients. In the paper, we show how to avoid these difficulties using empirical formulae based on lexical-grammatical properties of a text. Such formulae are trained on given set of examples, which are evaluated manually by an expert(s) and the best formula is selected by the Ivakhnenko Method of Model Self-Organization. We test the suggested methodology on the real set of dialogues from Barcelona railway directory inquiries for estimation of passenger’s politeness.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Mikhail Alexandrov
    • 1
  • Xavier Blanco
    • 1
  • Natalia Ponomareva
    • 2
  • Paolo Rosso
    • 2
  1. 1.Universidad Autonoma de BarcelonaSpain
  2. 2.Universidad Politecnica de ValenciaSpain

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