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Article

Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence †

Group of Multimedia Processing, Signal Theory and Communications Department, University Carlos III Madrid, 28911 Leganés, Madrid, Spain
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the IBER Speech Conference, Barcelona, Spain, 21–23 November 2018.
Appl. Sci. 2019, 9(11), 2298; https://doi.org/10.3390/app9112298
Received: 1 March 2019 / Revised: 1 May 2019 / Accepted: 24 May 2019 / Published: 4 June 2019
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
Keywords: speaker identification; emotions; stress conditions; data augmentation; synthetic stress speaker identification; emotions; stress conditions; data augmentation; synthetic stress
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MDPI and ACS Style

Rituerto-González, E.; Mínguez-Sánchez, A.; Gallardo-Antolín, A.; Peláez-Moreno, C. Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence. Appl. Sci. 2019, 9, 2298. https://doi.org/10.3390/app9112298

AMA Style

Rituerto-González E, Mínguez-Sánchez A, Gallardo-Antolín A, Peláez-Moreno C. Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence. Applied Sciences. 2019; 9(11):2298. https://doi.org/10.3390/app9112298

Chicago/Turabian Style

Rituerto-González, Esther, Alba Mínguez-Sánchez, Ascensión Gallardo-Antolín, and Carmen Peláez-Moreno. 2019. "Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence" Applied Sciences 9, no. 11: 2298. https://doi.org/10.3390/app9112298

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