Rituerto González, EstherGallardo Antolín, AscensiónPeláez Moreno, Carmen2019-10-162019-10-162018-11Proceedings of IberSPEECH 2018, Pp. 15-19https://hdl.handle.net/10016/29035Proceeding of: IberSPEECH 2018, 21-23 November 2018, Barcelona, SpainSpeaker 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.5engSpeaker recognitionSpeaker identificationEmotionsStress conditionsData augmentationSynthetic stressconference paperElectrónicaTelecomunicacioneshttps://doi.org/10.21437/IberSPEECH.2018-4open access1519Proceedings of IberSPEECH 2018, 21-23 November 2018, Barcelona, SpainCC/0000028620