Emotion Recognition from Speech: Stress Experiment

Stefan Scherer, Hansjörg Hofmann, Malte Lampmann, Martin Pfeil, Steffen Rhinow, Friedhelm Schwenker, Günther Palm

Abstract
The goal of this work is to introduce an architecture to automatically detect the amount of stress in the speech signal close to real time. For this an experimental setup to record speech rich in vocabulary and containing different stress levels is presented. Additionally, an experiment explaining the labeling process with a thorough analysis of the labeled data is presented. Fifteen subjects were asked to play an air controller simulation that gradually induced more stress by becoming more difficult to control. During this game the subjects were asked to answer questions, which were then labeled by a different set of subjects in order to receive a subjective target value for each of the answers. A recurrent neural network was used to measure the amount of stress contained in the utterances after training. The neural network estimated the amount of stress at a frequency of 25 Hz and outperformed the human baseline.
Anthology ID:
L08-1082
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
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Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/336_paper.pdf
DOI:
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Cite (ACL):
Stefan Scherer, Hansjörg Hofmann, Malte Lampmann, Martin Pfeil, Steffen Rhinow, Friedhelm Schwenker, and Günther Palm. 2008. Emotion Recognition from Speech: Stress Experiment. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Emotion Recognition from Speech: Stress Experiment (Scherer et al., LREC 2008)
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http://www.lrec-conf.org/proceedings/lrec2008/pdf/336_paper.pdf
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