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

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 effec...

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Bibliographic Details
Published in:Applied sciences 2019-06, Vol.9 (11), p.2298
Main Authors: Rituerto-González, Esther, Mínguez-Sánchez, Alba, Gallardo-Antolín, Ascensión, Peláez-Moreno, Carmen
Format: Article
Language:English
Subjects:
Aggression
Assaults
Data augmentation
Emotions
Experimentation
Gender
Identification systems
International conferences
Neural networks
Physiology
Signal processing
Smartphones
Software
speaker identification
Speech
Speech recognition
Stress
stress conditions
synthetic stress
Violence
Voice recognition
Wearable technology
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Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app9112298