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Multimodal Emogram, Data Collection and Presentation

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Part of the book series: Cognitive Technologies ((COGTECH))

Summary

There are several characteristics not optimally suited for the user state classification with Wizard-of-Oz (WOZ) data like the nonuniform distribution of emotions in the utterances and the distribution of emotional utterances in speech, facial expression, and gesture. In particular, the fact that most of the data collected in the WOZ experiments are without any emotional expression gives rise to the problem of getting enough representative data for training the classifiers. Because of this problem we collected data in our own database. These data are also relevant for several demonstration sessions, where the functionality of the SmartKom system is shown in accordance with the defined use cases.

In the following we first describe the system environment for data collection and then the collected data. At the end we will discuss the tool to demonstrate user states detected in the different modalities.

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References

  • C. Frank, J. Adelhardt, A. Batliner, E. Nöth, R.P. Shi, V. Zeißler, and H. Niemann. The Facial Expression Module, 2006. In this volume.

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  • R.P. Shi, J. Adelhardt, A. Batliner, C. Frank, E. Nöth, V. Zeißler, and H. Niemann. The Gesture Interpretation Module, 2006. In this volume.

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  • M. Streit, A. Batliner, and T. Portele. Emotion Analysis and Emotion Handling Subdialogs, 2006. In this volume.

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  • V. Zeißler, J. Adelhardt, A. Batliner, C. Frank, E. Nöth, R.P. Shi, and H. Niemann. The Prosody Module, 2006. In this volume.

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© 2006 Springer-Verlag Berlin Heidelberg

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Adelhardt, J., Frank, C., Nöth, E., Shi, R.P., Zeißler, V., Niemann, H. (2006). Multimodal Emogram, Data Collection and Presentation. In: Wahlster, W. (eds) SmartKom: Foundations of Multimodal Dialogue Systems. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36678-4_36

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  • DOI: https://doi.org/10.1007/3-540-36678-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23732-7

  • Online ISBN: 978-3-540-36678-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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