
Esther Rituerto-GonzálezUniversity Carlos III de Madrid | UC3M · Department of Signal Theory and Communications
Esther Rituerto-González
Master of Engineering
About
10
Publications
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Introduction
She is pursuing a Ph.D. in Speaker Recognition under emotional conditions. Her current research interests include speech technologies, affective and cognitive computing and deep learning.
Additional affiliations
Education
November 2019 - May 2022
October 2017 - June 2018
September 2013 - October 2017
Publications
Publications (10)
Although running is a common leisure activity and a core training regiment for several athletes, between $29\%$ and $79\%$ of runners sustain an overuse injury each year. These injuries are linked to excessive fatigue, which alters how someone runs. In this work, we explore the feasibility of modelling the Borg received perception of exertion (RPE)...
Among the seventeen Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13$^{th}$ SDG is a call for action to combat climate change for a better world. In this work, we provide an overview of areas in which audio intelligence -- a powerful but in this context so far hardly co...
Among the seventeen Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the Fifth SDG is a call for action to turn Gender Equality into a fundamental human right and an essential foundation for a better world. It includes the eradication of all types of violence against women. Wi...
Speech ‘in-the-wild’ is a handicap for speaker recognition systems due to the variability induced by real-life conditions, such as environmental noise and the emotional state of the speaker. Taking advantage of the principles of representation learning, we aim to design a recurrent denoising autoencoder that extracts robust speaker embeddings from...
Currently, most of the affective computing research is about modifying and adapting the machine behavior based on the human emotional state. Although, the use of the affective state inference can be extended to provide a tool for other fields more society related such as gender violence detection, which is a real global emergency. Based on the Worl...
Speech 'in-the-wild' is a handicap for speaker recognition systems due to the variability induced by real-life conditions, such as environmental noise and emotions in the speaker. Taking advantage of representation learning, on this paper we aim to design a recurrent denoising autoencoder architecture that extracts robust low-dimensional representa...
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 mitiga...