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J. Higueras-Soler, R. Gil-Pita, E. Alexandre, and M. Rosa-Zurera, "Violence Prediction through Emotional Speech," Paper 8003, (2010 May.). doi: J. Higueras-Soler, R. Gil-Pita, E. Alexandre, and M. Rosa-Zurera, "Violence Prediction through Emotional Speech," Paper 8003, (2010 May.). doi:
Abstract: Preventing violence takes an absolute necessity in our society. Whether in homes with a particular risk of domestic violence, as in prisons or schools, there is a need for systems capable of detecting risk situations, for preventive purposes. One of the most important factors that precede a violent situation is an emotional state of anger. In this paper we discuss the features that are required to provide decision makers dedicated to the detection of emotional states of anger from speech signals. For this purpose, we present a set of experiments and results with the aim of studying the combination of features extracted from the literature and their effects over the detection performance (relationship between probability of detection of anger and probability of false alarm) of a neural network and a least-square linear detector.

@article{higueras-soler2010violence,
author={higueras-soler, josé and gil-pita, roberto and alexandre, enrique and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={violence prediction through emotional speech},
year={2010},
volume={},
number={},
pages={},
doi={},
month={may},} @article{higueras-soler2010violence,
author={higueras-soler, josé and gil-pita, roberto and alexandre, enrique and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={violence prediction through emotional speech},
year={2010},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={preventing violence takes an absolute necessity in our society. whether in homes with a particular risk of domestic violence, as in prisons or schools, there is a need for systems capable of detecting risk situations, for preventive purposes. one of the most important factors that precede a violent situation is an emotional state of anger. in this paper we discuss the features that are required to provide decision makers dedicated to the detection of emotional states of anger from speech signals. for this purpose, we present a set of experiments and results with the aim of studying the combination of features extracted from the literature and their effects over the detection performance (relationship between probability of detection of anger and probability of false alarm) of a neural network and a least-square linear detector.},}

TY - paper
TI - Violence Prediction through Emotional Speech
SP - EP -
AU - Higueras-Soler, José
AU - Gil-Pita, Roberto
AU - Alexandre, Enrique
AU - Rosa-Zurera, Manuel
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2010 TY - paper
TI - Violence Prediction through Emotional Speech
SP - EP -
AU - Higueras-Soler, José
AU - Gil-Pita, Roberto
AU - Alexandre, Enrique
AU - Rosa-Zurera, Manuel
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2010
AB - Preventing violence takes an absolute necessity in our society. Whether in homes with a particular risk of domestic violence, as in prisons or schools, there is a need for systems capable of detecting risk situations, for preventive purposes. One of the most important factors that precede a violent situation is an emotional state of anger. In this paper we discuss the features that are required to provide decision makers dedicated to the detection of emotional states of anger from speech signals. For this purpose, we present a set of experiments and results with the aim of studying the combination of features extracted from the literature and their effects over the detection performance (relationship between probability of detection of anger and probability of false alarm) of a neural network and a least-square linear detector.