Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech

We propose a study of the mathematical properties of voice as an audio signal -- This work includes signals in which the channel conditions are not ideal for emotion recognition -- Multiresolution analysis- discrete wavelet transform – was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states -- ANNs proved to be a system that allows an appropriate classification of such states -- This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features -- Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify

• Autores: Campo, D.; Quintero, O.L.; Bastidas, M; Campo, D.; Quintero, O.L.; Bastidas, M
• Fecha de publicación: 2016
• Institución: Universidad EAFIT
• Repositorio: Repositorio EAFIT
• Idioma: eng
• OAI Identifier: oai:repository.eafit.edu.co:10784/8374
• Acceso en línea: http://hdl.handle.net/10784/8374
• Palabra clave: Transformadas de Wavelet; Análisis Multi - Resolución; Procesamiento digital de voz; RECONOCIMIENTO AUTOMÁTICO DE LA VOZ; PROCESAMIENTO DE SEÑALES; INTELIGENCIA ARTIFICIAL; EMOCIONES; ANÁLISIS ESPECTRAL; REDES NEURALES (COMPUTADORES); ANÁLISIS DE FOURIER; INTELIGENCIA ARTIFICIAL; Automatic speech recognition; Signal processing; Artificial intelligence; Emotions; Spectrum analysis; Neural networks (Computer science); Fourier analysis; Artificial intelligence; Automatic speech recognition; Signal processing; Artificial intelligence; Emotions; Spectrum analysis; Neural networks (Computer science); Fourier analysis; Artificial intelligence; Transformadas de Wavelet; Análisis Multi - Resolución; Procesamiento digital de voz
• License: Acceso abierto