2026-04-13T01:22:13Zhttps://recercat.cat/oai/requestoai:recercat.cat:10230/308252025-12-21T18:05:29Zcom_2072_6col_2072_452952
RECERCAT
author
Farrús, Mireia
author
Ejarque, Pascual
author
Temko, Andrey
author
Hernando, Javier
2017-04-18T08:23:54Z2017-04-18T08:23:54Z2007
Comunicació presentada a la International Conference on Biometrics (ICB) celebrada a Seoul (Korea) els dies 27 a 29 d'agost de 2007.It has been shown that prosody helps to improve voice spectrum based speaker recognition systems. Therefore, prosodic features can also be used in multimodal person verification in order to achieve better results. In this paper, a multimodal recognition system based on facial and vocal tract spectral features is improved by adding prosodic information. Matcher weighting method and support vector machines have been used as fusion techniques, and histogram equalization has been applied before SVM fusion as a normalization technique. The results show that the performance of a SVM multimodal verification system can be improved by using histogram equalization, especially when the equalization is applied to those scores giving the highest EER values.
© Springer The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-540-74549-5_86. info:eu-repo/semantics/openAccess
Speaker recognition
Multimodality
Fusion
Support vector machines
Histogram equalization
Prosody
Voice spectrum
Face
Histogram equalization in SVM multimodal person verification
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion