Double Fourier analysis for Emotion Identification in Voiced Speech. (April 2016)

• Record Type: Journal Article
• Authors: Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O.L.
• Is Part Of: Journal of physics. Volume 705(2016)
• Publication Date: 2016-04
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/705/1/012035
• Languages: English
• ISSNs: 1742-6588

Abstract

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.