%0 Book Section %1 Boeck2011ACII %A Böck, Ronald %A Siegert, Ingo %A Haase, Matthias %A Lange, Julia %A Wendemuth, Andreas %B Affective Computing and Intelligent Interaction. %D 2011 %E D'Mello, Sidney %E Graesser, Arthur %E Schuller, Björn %E Martin, Jean-Claude %I Springer Berlin, Heidelberg %K conferencebook %P 25--34 %R 10.1007/978-3-642-24600-5 %T ikannotate - A Tool for Labelling, Transcription, and Annotation of Emotionally Coloured Speech %V 6974 %X 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.

@incollection{Boeck2011ACII, 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.}, added-at = {2018-10-05T10:33:04.000+0200}, author = {B{\"o}ck, Ronald and Siegert, Ingo and Haase, Matthias and Lange, Julia and Wendemuth, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2bba78f425e40a90efb412cb9319f34ad/isiegert}, booktitle = {Affective Computing and Intelligent Interaction.}, doi = {10.1007/978-3-642-24600-5}, editor = {D'Mello, Sidney and Graesser, Arthur and Schuller, Bj{\"o}rn and Martin, Jean-Claude}, interhash = {8128a308d5b4a14b89cd404de1106182}, intrahash = {bba78f425e40a90efb412cb9319f34ad}, keywords = {conferencebook}, pages = {25--34}, publisher = {Springer Berlin, Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2018-10-05T10:33:15.000+0200}, title = {ikannotate - A Tool for Labelling, Transcription, and Annotation of Emotionally Coloured Speech}, volume = 6974, year = 2011 }