Data augmentation for speaker identification under stress conditions to combat gender-based violence
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Authors
Rituerto-González, Esther
Mínguez-Sánchez, Alba
Gallardo-Antolín, Ascensión
Peláez-Moreno, Carmen
Issue Date
2019-06-04
Type
Article
Language
en_US
Keywords
Speaker Identification , Emotions , Stress Conditions , Data Augmentation , Synthetic Stress
Alternative Title
Abstract
A Speaker Identification system for a personalized wearable device to combat gender-based violence is presented in this paper. Speaker recognition systems exhibit a decrease in performance when the user is under emotional or stress conditions, thus the objective of this paper is to measure the effects of stress in speech to ultimately try to mitigate their consequences on a speaker identification task, by using data augmentation techniques specifically tailored for this purpose given the lack of data resources for this condition. An extensive experimentation has been carried out for assessing the effectiveness of the proposed techniques. First, we conclude that the best performance is always obtained when naturally stressed samples are included in the training set, and second, when these are not available, their substitution and augmentation with synthetically generated stress-like samples improves the performance of the system. View Full-Text
Description
Citation
Rituerto-González, E., Mínguez-Sánchez, A., Gallardo-Antolín, A., & Peláez-Moreno, C. (2019). Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence. Applied Sciences, 9(11), 2298. MDPI AG. http://dx.doi.org/10.3390/app9112298
Publisher
Applied Sciences