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Double Fourier analysis for Emotion Identification in Voiced Speech

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JPCS_705_1_012035.pdf (1.777Mb)
Date
2016
Author
Sierra-Sosa, D
Bastidas, M
Ortiz P., D.
Quintero, O.L.
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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
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URI
http://dx.doi.org/10.1088/1742-6596/705/1/012035
http://hdl.handle.net/10784/8375
Editor URL
Journal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9
DOI
10.1088/1742-6596/705/1/012035
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