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Voice conversion - the methodology of automatically converting one's utterances to sound as if spoken by another speaker - presents a threat for applications relying on speaker verification. We study vulnerability of text-independent speaker verification systems against voice conversion attacks using telephone speech. We implemented a voice conversion systems with two types of features and nonparallel...
We propose a Near-Duplicate Keyframe (NDK) retrieval method that can handle extreme zooming and significant object motion. The first stage consists of eliminating false keypoint matches using symmetric property and a ratio of nearest and second-nearest neighbor distances. Then, a pattern coherency score is assigned to each pair of keyframes. These two features are combined through linear discriminant...
In this paper, we propose a subspace construction and selection strategy (SUBS) for speaker recognition with limited training and testing speech data. Based on the individual Gaussian distributions of Gaussian mixture model (GMM), each speaker's characteristic subspace is constructed by training an SVM using the corresponding Gaussian mean vectors from the GMMs of both enrollment and imposter speakers...
In this paper, we study speaker characterization using prosodic supervectors with negative within-class covariance normalization (NWCCN) projection and speaker modeling with support vector regression (SVR). We also propose a segmental weight fusion (SWF) technique that combines acoustic and prosodic subsystems effectively, despite the big performance gap between the subsystems. We validate the effectiveness...
This paper describes the performance of the I4U speaker recognition system in the NIST 2008 Speaker Recognition Evaluation. The system consists of seven subsystems, each with different cepstral features and classifiers. We describe the I4U Primary system and report on its core test results as they were submitted, which were among the best-performing submissions. The I4U effort was led by the Institute...
This paper presents a novel approach of discriminative acoustic feature extraction for speech recognition using output coding technique. A high dimensional feature space for higher discriminative capability is constructed by expanding MFCC coefficients with polynomial expansion. In order to fit the discriminative features in the hidden Markov model structure of speech recognition, the high dimensional...
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