Luis Miguel Mazaira-Fernández

Universidad Politécnica de Madrid

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i-10 index

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Co-Authors

Pedro Gómez‐Vilda

Universidad Politécnica de Madrid

AÁ

Agustín Álvarez-Marquina

Universidad Politécnica de Madrid

R. Martínez

Universidad Politécnica de Madrid

Cristina Muñoz-Mulas

Universidad Politécnica de Madrid

V. Rodellar

Universidad Politécnica de Madrid

José Manuel Ferrández Vicente

Universidad Politécnica de Cartagena

Victor Nieto‐Lluis

Universidad Politécnica de Madrid

Carlos Ramírez-Calvo

Hospital Universitario del Henares

Mario Fernández‐Fernández

University of Talca

Roberto Fernández-Baíllo

Universidad Europea

Cooperative Institutions

Universidad Politécnica de Madrid

Universidad Politécnica de Cartagena

Hospital General Universitario Gregorio Marañón

Centro Tecnológico de Investigación, Desarrollo e Innovación en tecnologías de la Información y las Comunicaciones (TIC)

Polytechnic University of Puerto Rico

Hospital Universitario del Henares

Universidad de Alcalá

Universidad Rey Juan Carlos

University of Buenos Aires

Comunidad de Madrid

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Neurological Disease Detection and Monitoring from Voice Production

Lecture notes in computer science (2011)

Pedro Gómez‐Vilda V. Rodellar Victor Nieto‐Lluis Cristina Muñoz-Mulas Luis Miguel Mazaira-Fernández

10.1007/978-3-642-25020-0_1

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Citations (10)

Improving Speaker Recognition by Biometric Voice Deconstruction

Frontiers in Bioengineering and Biotechnology (2015)

Luis Miguel Mazaira-Fernández Agustín Álvarez-Marquina Pedro Gómez‐Vilda

Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.

Identification

Deconstruction (building)

Feature (linguistics)

Mel-frequency cepstrum

Vocal tract

10.3389/fbioe.2015.00126

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Citations (15)

New Method for Finding Optimum Number of Characteristics to Classify Speakers by Age

Smart innovation, systems and technologies (2016)

Cristina Muñoz-Mulas R. Martínez Pedro Gómez‐Vilda Agustín Álvarez-Marquina Luis Miguel Mazaira-Fernández

Rank (graph theory)

Bootstrapping (finance)

Feature (linguistics)

10.1007/978-3-319-28109-4_29

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Citations (0)

Neuromorphic detection of speech dynamics

Neurocomputing (2010)

Pedro Gómez‐Vilda José Manuel Ferrández Vicente V. Rodellar Agustín Álvarez-Marquina Luis Miguel Mazaira-Fernández

Neuromorphic engineering

10.1016/j.neucom.2010.07.023

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Citations (10)

Neuromorphic Detection of Vowel Representation Spaces

Lecture notes in computer science (2011)

Pedro Gómez‐Vilda José Manuel Ferrández Vicente V. Rodellar Agustín Álvarez-Marquina Luis Miguel Mazaira-Fernández

Neuromorphic engineering

Keyword spotting

Representation

Spotting

10.1007/978-3-642-21326-7_1

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Citations (2)

Neuromorphic Speech Processing

IGI Global eBooks (2010)

Pedro Gómez‐Vilda José Manuel Ferrández Vicente V. Rodellar R. Martínez Victor Nieto‐Lluis

Current trends in the search for improvements in well-established technologies imitating human abilities, as speech perception, try to find inspiration in the explanation of certain capabilities hidden in the natural system which are not yet well understood. A typical case is that of speech recognition, where the semantic gap going from spectral time-frequency representations to the symbolic translation into phonemes and words, and the construction of morpho-syntactic and semantic structures find many hidden phenomena not well understood yet. The present chapter is intended to explore some of these facts at a simplifying level under two points of view: that of top-down analysis provided from speech perception, and the symmetric from bottom-up synthesis provided by the biological architecture of auditory pathways. An application-driven design of a Neuromorphic Speech Processing Architecture is presented and its performance analyzed. Simulation details provided by a parallel implementation of the architecture in a supercomputer will be also shown and discussed.

Neuromorphic engineering

10.4018/978-1-61520-919-4.ch019

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Citations (0)

Estimating Tremor in Vocal Fold Biomechanics for Neurological Disease Characterization

Pedro Gómez‐Vilda Victor Nieto‐Lluis V. Rodellar Agustín Álvarez-Marquina Luis Miguel Mazaira-Fernández

Neurological Diseases (ND) are affecting larger segments of aging population every year. Treatment is dependent on expensive accurate and frequent monitoring. It is well known that ND leave correlates in speech and phonation. The present work shows a method to detect alterations in vocal fold tension during phonation. These may appear either as hypertension or as cyclical tremor. Estimations of tremor may be produced by auto-regressive modeling of the vocal fold tension series in sustained phonation. The correlates obtained are a set of cyclicality coefficients, the frequency and the root mean square amplitude of the tremor. Statistical distributions of these correlates obtained from a set of male and female subjects are presented. Results from five study cases of female voice are also given.

Biomechanics

10.1109/icdsp.2013.6622735

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Citations (8)

Characterizing Neurological Disease from Voice Quality Biomechanical Analysis

Cognitive Computation (2013)

Pedro Gómez‐Vilda V. Rodellar Victor Nieto‐Lluis Cristina Muñoz-Mulas Luis Miguel Mazaira-Fernández

Grading (engineering)

10.1007/s12559-013-9207-2

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Citations (31)

Detecting pathology in the glottal spectral signature of female voice.