@inproceedings{scherer-etal-2008-emotion,
title = "Emotion Recognition from Speech: Stress Experiment",
author = {Scherer, Stefan and
Hofmann, Hansj{\"o}rg and
Lampmann, Malte and
Pfeil, Martin and
Rhinow, Steffen and
Schwenker, Friedhelm and
Palm, G{\"u}nther},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/336_paper.pdf",
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.",
}
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%0 Conference Proceedings
%T Emotion Recognition from Speech: Stress Experiment
%A Scherer, Stefan
%A Hofmann, Hansjörg
%A Lampmann, Malte
%A Pfeil, Martin
%A Rhinow, Steffen
%A Schwenker, Friedhelm
%A Palm, Günther
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F scherer-etal-2008-emotion
%X 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.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/336_paper.pdf
Markdown (Informal)
[Emotion Recognition from Speech: Stress Experiment](http://www.lrec-conf.org/proceedings/lrec2008/pdf/336_paper.pdf) (Scherer et al., LREC 2008)
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).