Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10495/5747
Título : Emotion Recognition from Speech with Acoustic, Non-Linear and Wavelet-based Features Extracted in Different Acoustic Conditions
Autor : Vásquez Correa, Juan Camilo
metadata.dc.contributor.advisor: Vargas Bonilla, Jesús Francisco
metadata.dc.subject.*: Análisis acústico
Procesamiento de voz no lineal
Reconocimiento de emociones
Fecha de publicación : 2016
Citación : Vásquez Correa, J. C. (2016). Emotion Recognition from Speech with Acoustic, Non-Linear and Wavelet-based Features Extracted in Different Acoustic Conditions (Tesis de maestría). Universidad de Antioquia, Medellín. Colombia.
Resumen : ABSTRACT: In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called "paralinguistic" aspects of the speech, including the emotions, and the personality of the speaker. This research work aims in the development of a methodology for the automatic emotion recognition from speech signals in non-controlled noise conditions. For that purpose, different sets of acoustic, non-linear, and wavelet based features are used to characterize emotions in different databases created for such purpose.
Aparece en las colecciones: Maestrías en Ingeniería

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