Memorias de investigación
Research Publications in journals:
Gender Detection in Running Speech from Glottal and Vocal Tract Correlates
Year:2013

Research Areas
  • Processing and signal analysis

Information
Abstract
Gender detection from running speech is a very important objective to improve efficiency in tasks as speech or speaker recognition, among others. Traditionally gender detection has been focused on fundamental frequency (f0) and cepstral features derived from voiced segments of speech. The methodology presented here discards f0 as a valid feature because its estimation is complicate, or even impossible in unvoiced fragments, and its relevance in emotional speech or in strongly prosodic speech is not reliable. The approach followed consists in obtaining uncorrelated glottal and vocal tract components which are parameterized as mel-frequency coefficients. K-fold and cross-validation using QDA and GMM classifiers showed detection rates as large as 99.77 in a gender-balanced database of running speech from 340 speakers.
International
Si
JCR
No
Title
Lecture Notes on Artificial Intelligence
ISBN
0302-9743
Impact factor JCR
Impact info
Volume
7911
Journal number
From page
25
To page
32
Month
SIN MES
Ranking
Participants

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