Title :
GMM and kernel-based speaker recognition with the ISIP toolkit
Author :
Imbiriba, T. ; Klautau, Aldeharo ; Pariha, Naveen ; Raghavan, Sridhar ; Picone, Joseph
Author_Institution :
Signal Process. Lab., Universidade Federal do Para
fDate :
Sept. 29 2004-Oct. 1 2004
Abstract :
This paper describes an open source framework for developing speaker recognition systems. Among other features, it supports kernel classifiers, such as the support and relevance vector machines. The paper also presents results for the IME corpus using Gaussian mixture models, which outperforms previously published ones, and discusses strategies for applying discriminative classifiers to speaker recognition
Keywords :
Gaussian processes; speaker recognition; support vector machines; GMM-based speaker recognition; Gaussian mixture models; IME corpus; ISIP toolkit; discriminative classifiers; kernel classifiers; kernel-based speaker recognition; open source framework; relevance vector machines; support vector machines; Computer architecture; Hidden Markov models; Kernel; Maximum likelihood linear regression; Production systems; Signal processing; Speaker recognition; Speech recognition; Support vector machine classification; Support vector machines;
Conference_Titel :
Machine Learning for Signal Processing, 2004. Proceedings of the 2004 14th IEEE Signal Processing Society Workshop
Conference_Location :
Sao Luis
Print_ISBN :
0-7803-8608-4
DOI :
10.1109/MLSP.2004.1422996
