Constructing Empirical Models for Automatic Dialog Parameterization

Automatic classification of dialogues between clients and a service center needs a preliminary dialogue parameterization. Such a parameterization is usually faced with essential difficulties when we deal with politeness, competence, satisfaction, and other similar characteristics 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.

• Type: Conference
• Year: 2007
• Where: TSD
• Authors: Mikhail Alexandrov, Xavier Blanco, Natalia Ponomareva, Paolo Rosso
• Keywords: Dialogues, Essential Difficulties, Preliminary Dialogue Parameterization, Signal Processing, TSD 2007