Publication: Speaker recognition under stress conditions
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2018-11
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Abstract
Speaker recognition systems exhibit a decrease in performance when the input speech is not in optimal circumstances, for example when the user is under emotional or stress conditions. The objective of this paper is measuring the effects of stress on speech to ultimately try to mitigate its consequences on a speaker recognition task. On this paper, we develop a stress-robust speaker identification system using data selection and augmentation by means of the manipulation of the original speech utterances. An extensive experimentation has been carried out for assessing the effectiveness of the proposed techniques. First, we concluded 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.
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Proceeding of: IberSPEECH 2018, 21-23 November 2018, Barcelona, Spain
Keywords
Speaker recognition, Speaker identification, Emotions, Stress conditions, Data augmentation, Synthetic stress
Bibliographic citation
Proceedings of IberSPEECH 2018, Pp. 15-19