Double Fourier analysis for Emotion Identification in Voiced Speech
Fecha
2016
Título de la revista
ISSN de la revista
Título del volumen
Editor
IOP Publishing
Resumen
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
Descripción
Palabras clave
Transformadas de Wavelet, Procesamiento digital de voz, Morfología matemática