Visual tag dictionary: interpreting tags with visual words
WSMC '09 Proceedings of the 1st workshop on Web-scale multimedia corpus
Robust speaker identification system based on wavelet transform and gaussian mixture model
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
HCRF-UBM approach for text-independent speaker identification
Computers & Mathematics with Applications
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We describe a novel discriminative training procedure for a Gaussian mixture model (GMM) speaker identification system. The proposal is based on the segmental generalized probabilistic descent (GPD) algorithm formulated to estimate the GMM parameters. Two major innovations over similar formulations of segmental GPD training are proposed. (1) A misclassification measure based on an individual representation of competing speakers, that explicitly allows to take into account different learning strategies for correctly or incorrectly classified speakers. (2) An empirical loss function to control the training procedure convergence, with a likelihood-based selection of correctly or incorrectly classified competing speakers. A comparison between the proposed method and the traditional GPD algorithm is also presented.