2016-05-1120161742-6596http://hdl.handle.net/10784/8375We 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 presentedapplication/pdfengTransformadas de WaveletProcesamiento digital de vozMorfología matemáticainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessANÁLISIS ESPECTRALANÁLISIS DE FOURIERPROCESAMIENTO DE SEÑALESSISTEMAS DE PROCESAMIENTO DE LA VOZTRANSFORMACIONES (MATEMÁTICAS)PRINCIPIO DE INCERTIDUMBRE DE HEISENBERGSpectrum analysisFourier analysisSignal processingSpeech processing systemsTransformations (mathematics)Heisenberg uncertainty principleSpectrum analysisFourier analysisSignal processingSpeech processing systemsTransformations (mathematics)Heisenberg uncertainty principleTransformadas de WaveletProcesamiento digital de vozMorfología matemáticaAcceso abierto2016-05-11Creative Commons Attribution 3.0 licence (CC BY 3.0)Sierra-Sosa, DBastidas, MOrtiz P., D.Quintero, O.L.Sierra-Sosa, DBastidas, MOrtiz P., D.Quintero, O.L.10.1088/1742-6596/705/1/012035