Journal article
D. Sierra-Sosa, M. Bastidas, D. Ortiz, O. Quintero
2016
2016
Semantic Scholar
DOI
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Cite
APA
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Sierra-Sosa, D., Bastidas, M., Ortiz, D., & Quintero, O. (2016). Double Fourier analysis for Emotion Identification in Voiced Speech.
Chicago/Turabian
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Sierra-Sosa, D., M. Bastidas, D. Ortiz, and O. Quintero. “Double Fourier Analysis for Emotion Identification in Voiced Speech” (2016).
MLA
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Sierra-Sosa, D., et al. Double Fourier Analysis for Emotion Identification in Voiced Speech. 2016.
BibTeX Click to copy
@article{d2016a,
title = {Double Fourier analysis for Emotion Identification in Voiced Speech},
year = {2016},
author = {Sierra-Sosa, D. and Bastidas, M. and Ortiz, D. and Quintero, O.}
}
Abstract
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.