I. Mohíno-Herranz, S. ,. C. Llerena-Aguilar, J. García-Gómez, M. Utrilla-Manso, and M. Rosa-Zurera, “Precision Maximization in Anger Detection in Interactive Voice Response Systems,” in Proc. AES Convention 145, Oct. 2018, Paper 10090. [Online]. Available: https://aes.org/publications/elibrary-page/?id=19816
Mohíno-Herranz I, Llerena-Aguilar S,C, García-Gómez J, Utrilla-Manso M, Rosa-Zurera M. Precision Maximization in Anger Detection in Interactive Voice Response Systems. In: AES Convention 145. Audio Engineering Society; 2018. Paper 10090. Available from: https://aes.org/publications/elibrary-page/?id=19816
@inproceedings{MohinoHerranz2018_19816,
author = {Mohíno-Herranz, Inma and Llerena-Aguilar, Sr., Cosme and García-Gómez, Joaquín and Utrilla-Manso, Manuel and Rosa-Zurera, Manuel},
title = {{Precision Maximization in Anger Detection in Interactive Voice Response Systems}},
booktitle = {AES Convention 145},
note = {Paper 10090},
year = {2018},
month = oct,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=19816}
}
TY - CPAPER
TI - Precision Maximization in Anger Detection in Interactive Voice Response Systems
AU - Mohíno-Herranz, Inma
AU - Llerena-Aguilar, Sr., Cosme
AU - García-Gómez, Joaquín
AU - Utrilla-Manso, Manuel
AU - Rosa-Zurera, Manuel
T2 - AES Convention 145
M1 - Paper 10090
PY - 2018
DA - 2018/10/06
UR - https://aes.org/publications/elibrary-page/?id=19816
PB - Audio Engineering Society
LA - en
AB - Detection is usually carried out following the Neyman-Pearson criterion to maximize the probability of detection (true positives rate), maintaining the probability of false alarm (false positives rate) below a given threshold. When the classes are unbalanced, the performance cannot be measured just in terms of true positives and false positives rates, and new metrics must be introduced, such as Precision. “Anger detection” in Interactive Voice Response (IVR) systems is one application where precision is important. In this paper a cost function for features selection to maximize precision in anger detection applications is presented. The method has been proved with a real database obtained by recording calls managed by an IVR system, demonstrating its suitability.
ER -