Abstract
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.
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Acknowledgments
The work presented in this paper was partially supported by the DAAD (German Academic Exchange Service), the Ministry of Education and Science of Russian Federation within project 28.697.2016/2.2, and the Transregional Collaborative Research Centre SFB/TRR 62 “Companion-Technology for Cognitive Technical Systems” which is funded by the German Research Foundation (DFG).
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Spirina, A., Skorokhod, A., Karaseva, T., Polonskaia, I., Sidorov, M. (2017). Significance of Interaction Parameter Levels in Interaction Quality Modelling for Human-Human Conversation. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_52
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