Linguistic Models Construction and Analysis for Satisfaction Estimation

Automatic analysis of customer conversations would be beneficial for service companies to improve service quality. In this case, such customer characteristics as satisfaction or competence are of the special interest. Unfortunately, their manual estimation is very laborious and it has a high level of subjectivity. In this work, we aim at parameterization of dialogues for formal (automatic) assessment of customer satisfaction. We elaborate a set of linguistic indicators represented both by lexico-syntactic patterns and rules and introduce their classification by kind, location and sign. We propose several linear regression models for satisfaction estimation and check them and their parameters on statistical significance. The best of the models demonstrates rather high level of concordance between automatic and manual assessments.