ikannotate - a tool for labelling, transcription, and annotation of emotionally coloured speech

Authors:
Ronald Böck;Ingo Siegert;Matthias Haase;Julia Lange;Andreas Wendemuth
Affiliations:
Otto von Guericke University, Dept. of Electrical Engineering and Information Technology, Magdeburg, Germany;Otto von Guericke University, Dept. of Electrical Engineering and Information Technology, Magdeburg, Germany;Otto von Guericke University, Dept. of Psychosomatic Medicine and Psychotherapy, Magdeburg, Germany;Otto von Guericke University, Dept. of Psychosomatic Medicine and Psychotherapy, Magdeburg, Germany;Otto von Guericke University, Dept. of Electrical Engineering and Information Technology, Magdeburg, Germany
Venue:
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Year:
2011

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Abstract

In speech recognition and emotion recognition from speech, qualitatively high transcription and annotation of given material is important. To analyse prosodic features, linguistics provides several transcription systems. Furthermore, in emotion labelling different methods are proposed and discussed. In this paper, we introduce the tool ikannotate, which combines prosodic information with emotion labelling. It allows the generation of a transcription of material directly annotated with prosodic features. Moreover, material can be emotionally labelled according to Basic Emotions, the Geneva Emotion Wheel, and Self Assessment Manikins. Finally, we present results of two usability tests observing the ability to identify emotions in labelling and comparing the transcription tool "Folker" with our application.