author = {Ingo Siegert and Andreas Wendemuth},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2017},
title = {ikannotate2 – A Tool Supporting Annotation of Emotions in Audio- Visual Data},
year = {2017},
editor = {Jürgen Trouvain and Ingmar Steiner and Bernd Möbius},
month = mar,
pages = {17--24},
publisher = {TUDpress, Dresden},
abstract = {For emotional analyses of interactions, qualitatively high transcription and annotation of given material is important. The textual transcription can be conducted with several available tools, like e.g. Folker or ANVIL. But tools for the annotation of emotions are quite rare. Furthermore, existing tools only allow to select an emotion term from a list of terms. Thus, a relation between the different emotional terms that has been uncovered by psychologists get lost. In this paper, we present an enhanced version of the tool ikannotate that is able to add an emotional annotation onto already transcribed material. This tool relies on established emotion labelling methods, like the Geneva Emotion Wheel or the Self Assessment Manikins to maintain the relationship. Furthermore, the annotator is guided by a step-wise process to improve the reliability of the emotional annotation. Additionally, the uncertainty in assessing emotions can be covered as well, to evaluate the labels afterwards and exclude samples with to low uncertainty from further analyses. The tool ikannotate2 can be used under Windows, Linux and macOS. All settings can be changed via corresponding INI-files.},
isbn = {978-3-959080-92-7},
issn = {0940-6832},
keywords = {Affektivität},
url = {https://www.essv.de/pdf/2017_17_24.pdf},