Examinando por Autor "Ortiz P., D."

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    Ítem
    Double Fourier analysis for Emotion Identification in Voiced Speech
    (IOP Publishing, 2016) Sierra-Sosa, D; Bastidas, M; Ortiz P., D.; Quintero, O.L.; Sierra-Sosa, D; Bastidas, M; Ortiz P., D.; Quintero, O.L.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Universidad EAFIT. Escuela de Ciencias; dsierras@eafit.edu.co; Modelado Matemático
    We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech -- Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions -- A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds -- Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions -- Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it -- Finally features related with emotions in voiced speech are extracted and presented
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    Ítem
    A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
    (IOP Publishing, 2016) Ortiz P., D.; Villa, Luisa F.; Salazar, Carlos; Quintero, O.L.; Ortiz P., D.; Villa, Luisa F.; Salazar, Carlos; Quintero, O.L.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Universidad EAFIT. Escuela de Ciencias; dpuerta1@eafit.edu.co; oquinte1@eafit.edu.co; Modelado Matemático
    A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works