Significance of Interaction Parameter Levels in Interaction Quality Modelling for Human-Human Conversation

摘要

The Interaction Quality (IQ) metric, which originally was designed for spoken dialogue systems (SDSs) to assess human-computer spoken interaction (HCSI) and then adapted to human-human conversation (HHC), is based on features from three interaction parameter levels: an exchange, a window, and a dialogue level. To determine the significance of the window and dialogue interaction parameter levels, as well as their combination, computations, based on different data sets, have been performed using several classification algorithms. The obtained results may be used for further improvement of the IQ model for HHC in terms of the computational complexity.