Language independent gender identification
- 24 December 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 685-688
- https://doi.org/10.1109/icassp.1996.543213
Abstract
This paper describes a novel technique specifically developed for gender identification which combines acoustic analysis and pitch. Two sets of hidden Markov models, male and female, are matched to the speech using the Viterbi algorithm and the most likely sequence of models with corresponding likelihood scores are produced. Linear discriminant analysis is used to normalise the models and reduce bias towards a particular gender. An enhanced version of the pitch estimation algorithm used for IMBE speech coding is used to give an average pitch estimate for the speaker. The information provided by the acoustic analysis and pitch estimation are combined using a linear classifier to identify the gender of the speech. The system was tested on three British English databases giving less than 1% identification error rate with two seconds of speech. Further tests without optimisation on eleven languages of the OGI database gave error rates less than 5.2% and an average of 2.0%.Keywords
This publication has 5 references indexed in Scilit:
- Speaker recognition in tactical communicationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Language identification using multiple knowledge sourcesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Cross-lingual experiments with phone recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- A speaker verification system using alpha-netsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- An investigation of PLP and IMELDA acoustic representations and of their potential for combinationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991