Abstract
Designing of indicators for problem detection during the dialogue is an important aspect for improving the systems user-adaptability in such rapidly expanding spheres as Spoken Dialogue Systems (SDSs) and Social Robotics (SR). Moreover, it is important not only for human-robot/computer spoken interaction (HCSI), but also for human-human conversation (HHC) as a way of service quality improvement in call centres. There are metrics, which may be used for both fields: HCSI and HHC. One of these metrics is customer/user satisfaction (CS), which modification is called Interaction Quality (IQ). Analysis of CS/IQ and human behaviour in some problematic situations (according to CS/IQ score) may be useful for further developing of an SDS that would be more human-like. Our research is focused on such essential parts of speech as emotions and overlapping speech. In this paper we analyse an impact of these speech features on automatic IQ estimation for HHC. Afterwards, we compare the obtained results with the result for HCSI.
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References
Schmitt, A., Schatz, B., Minker, W.: Modeling and predicting quality in spoken human-computer interaction. In: Proceedings of the SIGDIAL 2011 Conference, pp. 173–184. Association for Computational Linguistics (2011)
Spirina, A., Sidorov, M., Sergienko, R., Schmitt, A.: First experiments on interaction quality modelling for human-human conversation. In: Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO), vol. 2, pp. 374–380 (2016)
Wang, J.: From customer satisfaction to emotions: alternative framework to understand customer post-consumption behaviour. In: Proceedings of the 2012 International Joint Conference on Service Sciences, pp. 120–124 (2012)
Maar, B., Neely, A.: Managing and Measuring for Value: The Case of Call Centre Performance. Cranfield School of Management, UK (2004)
Park, Y., Gates, S.C.: Towards real-time measurement of customer satisfaction using automatically generated call transcripts. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 1387–1396 (2009)
Chowdhury, S.A., Stepanov, E.A., Riccardi, G.: Predicting user satisfaction from turn-talking in spoken conversations. In: Proceedings of INTERSPEECH 2016, pp. 2910–2914 (2016)
Schmitt, A., Ultes, S.: Interaction quality: assessing the quality of ongoing spoken dialog interaction by experts and how it relates to user satisfaction. Speech Commun. 74, 12–36 (2015)
Schmitt, A., Ultes, S., Minker, W.: A parameterized and annotated corpus of the CMU lets go bus information system. In: International Conference on Language Resources and Evaluation (LREC), pp. 3369–3373 (2012)
Ultes, S., Sanchez, M.J.P., Schmitt, A., Minker, W.: Analysis of an extended interaction quality corpus. In: Natural Language Dialog Systems and Intelligent Assistants, pp. 41–52 (2015)
Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1, 80–83 (1945)
Spirina, A.V., Sidorov, M.Y., Sergienko, R.B., Semenkin, E.S., Minker, W.: Human-human task-oriented conversations corpus for interaction quality modelling. Vestn. SibSAU 17(1), 84–90 (2016)
Eyben, F., Weninger, F., Gross, F., Schuller, B.: Recent developments in opensmile, the munich open-source multimedia feature extractor. In: Proceedings of ACM Multimedia (MM), pp. 835–838 (2013)
Schuller, B., Steidl, S., Batliner, A.: The interspeech 2009 emotion challenge. In: Proceedings of INTERSPEECH 2009, pp. 312–315 (2009)
Spirina, A., Minker, W., Sidorov, M.: Could emotions be beneficial for interaction quality modelling in human-human conversations? In: Proceedings of the 20th International Conference of Text, Speech and Dialogue (TSD2017) (2017)
Sidorov, M., Brester, C., Schmitt, A.: Contemporary stochastic feature selection algorithms for speech-based emotion recognition. In: Proceedings of INTERSPEECH 2015, pp. 2699–2703 (2015)
John, G.H., Langley, P.: Estimating continuous distribution in bayesian classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, pp. 338–345 (1995)
Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, USA (2011)
Abdi, H., Williams, L.J.: Principal component analysis. WIREs Comput. Stat. 2, 433–459 (2010)
le Cessie, S., Houwelingen, J.C.: Ridge estimators in logistic regression. Appl. Stat. 41(1), 191–201 (1992)
Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, Cambridge (2000)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer-Verlag, New York (1995)
Platt, J.: Fast training of support vector machines using sequential minimal optimization. In: Advances in Kernel Methods Support Vector Learning, vol. 3 (1999)
Rosenblatt, F.: Principles of Neurodynamics Perceptrons and the Theory of Brain Mechanisms. Spartan Books, Washingtion, D.C. (1961)
Gholap, J.: Performance tuning of J48 algorithm for prediction of soil fertility. Asian J. Comput. Sci. Inf. Technol. 2(8), 251–252 (2012)
Quinkan, J.R.: C4.5: Programs for Machime Learning. Morgan Kaufmann Publishers, Burlington (1993)
Spirina, A., Vaskovskaia, O., Sidorov, M., Schmitt, A.: Interaction quality as a human-human task-oriented conversation performance. In: Proceedings of the 18th International Conference on Speech and Computer (SPECOM 2016), pp. 403–410 (2016)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutmann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. 11(1), 10–18 (2009)
Goutte, C., Gaussier, E.: A probabilistic interpretation of precision, recall and F-score, with implication for evaluation. In: Advances in Information Retrieval, pp. 345–359 (2005)
Rosenberg, A.: Classifying skewed data: importance to optimize average recall. In: Proceedings of INTERSPEECH 2012, pp. 2242–2245 (2012)
Bailey, R.A.: Design of Comparative Experiments. Cambridge University Press, Cambridge (2008)
Kennedy, J.J., Bush, A.J.: An Introduction to the Design and Analysis of Experiments in Behavioural Research. University Press of America, Lanham (1985)
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., Vaskovskaia, O., Sidorov, M. (2017). Analysis of Overlapping Speech and Emotions for Interaction Quality Estimation. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2017. Lecture Notes in Computer Science(), vol 10459. Springer, Cham. https://doi.org/10.1007/978-3-319-66471-2_26
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DOI: https://doi.org/10.1007/978-3-319-66471-2_26
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