Observatorio de I+D+i UPM

Memorias de investigación
Thesis:
Speech Signals Feature Extraction Model for a Speaker?s Gender and Age Identification System
Year:2014
Research Areas
  • Information technology and adata processing
Information
Abstract
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.
International
Si
Type
Doctoral
Mark Rating
Sobresaliente
Date
14/11/2014
Participants
  • Director: Rafael Martinez Olalla (UPM)
  • Autor: Cristina Muñoz Mulas (Universidad Politécnica de Madrid)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Informática Aplicada al Procesado de Señal e Imagen
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)