@InProceedings{Böck2009_290,
author = {Ronald Böck and David Hübner and Andreas Wendemuth},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2009},
title = {On the Influences of Feature Extraction in Single Emotion Recognition in Naive vs. Acted Speech},
year = {2009},
editor = {Rüdiger Hoffmann},
month = mar,
pages = {207--214},
publisher = {TUDpress, Dresden},
abstract = {Generally, in communication several aspects have to be considered: 1) The communicated information itself, 2) the non-verbal information, i.e. poses and gestures, and 3) the emotional part of communication. All parts are necessary if a dialogue shall be successful and effective. Extracting the information from “what is said”, is the issue of the automatic speech recognition and, thus, provides the contents of a dialogue. The non-verbal information is usually faced by image processing and is not object of this paper. The last item is related to both. Hence, in this paper we focus on recognising emotions from speech. Therefore, we investigate the influences of different feature sets on emotion recognition. Moreover, we also compare two approaches of recognition: Hidden Markov Models and Artificial Neural Networks.},
isbn = {978-3-941298-31-6},
issn = {0940-6832},
keywords = {Sprachsynthese und Emotionsmodellierung},
url = {https://www.essv.de/pdf/pdf/2009_207_214.pdf},
}