Luis A. Hernández Gómez

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Smart cities have been recently pointed out by M2M experts as an emerging market with enormous potential, which is expected to drive the digital economy forward in the coming years. However, most of the current city and urban developments are based on vertical ICT solutions leading to an unsustainable sea of systems and market islands. In this work we(More)
This Thesis is focused on the use of automatic speaker recognition systems for forensic identification, in what is called forensic automatic speaker recognition. More generally, forensic identification aims at individualization, defined as the certainty of distinguishing an object or person from any other in a given population. This objective is followed by(More)
This Thesis is focused on the combination of multiple biometric traits for automatic person authentication, in what is called a multimodal biometric system. More generally, any type of biometric information can be combined in what is called a multibiometric system. The information sources in multibiometrics include not only multiple biometric traits but(More)
In accordance with the new emerging Voice Response Systems that use Flexible Vocabulary Recognizers (FVRs), prediction of word confusabilities have been received increasing interest during the last few years. In this contribution we present a new method for transcription confusabilities estimation based on a new statistical modelling criterion. We propose(More)
In this contribution we describe a novel discriminative training procedure for a Gaussian Mixture Model (GMM) Speaker Identification System. The proposal is based on the segmental Generalized Probabilistic Descent (GPD) algorithm formulated to estimate the GMM parameters. Two major innovations over similar formulations of segmental GPD training are(More)
This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can(More)
Ubiquitous Sensor Network (USN) concept describes the integration of heterogeneous and geographically dispersed Wireless Sensor and Actuator Networks (WS&AN) into rich information infrastructures for accurate representation and access to different dynamic user’s physical contexts. This relatively new concept envisions future Sensor-Based Services leading to(More)
This paper presents an algorithm for formant tracking using HMMs and analyzes the influence of HMM initialization, training and context-dependency on the accuracy of the formant tracks obtained with the HMMs. Formant trackers usually include two different phases: one in which the speech is analyzed and formant candidates are obtained, and another in which,(More)