Memorias de investigación
Tesis:
Speech Signals Feature Extraction Model for a Speaker?s Gender and Age Identification System
Año:2015

Áreas de investigación
  • Ciencias de la computación y tecnología informática

Datos
Descripción
Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker?s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.
Internacional
Si
ISBN
Tipo de Tesis
Doctoral
Calificación
Sobresaliente
Fecha
14/11/2014

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Participantes

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  • Creador: Grupo de Investigación: Informática Aplicada al Procesado de Señal e Imagen