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Predictive models for speaker verification
Speech Communication, 1993Abstract This paper outlines four novel methods for the task of speaker verification. The first model, a Hybrid Multi-Layer Perception (MLP)-Radial Basis Function (RBF) model, is an MLP predictor whose weights are then used as inputs to an RBF classifier for the verification process.
Eliathamby Ambikairajah +4 more
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Phoneme based speaker verification
[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992Text-independent speaker verification systems typically depend upon averaging over a long utterance to obtain a feature set for classification. However, not all speech is equally suited to the task of speaker verification. An approach to text-independent speaker verification that uses a two-stage classifier is presented.
Michael I. Savic, Jeffrey Sorensen
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Pattern recognition in speaker verification
Proceedings of the November 18-20, 1969, fall joint computer conference on - AFIPS '69 (Fall), 1969There are many ways in which a pattern recognition system may be implemented. In the specific problem of speaker verification, a two-class recognition scheme is of interest. A speaker who desired verification of his identity based upon some previously stored characteristics of his speech represents one of the two classes (real), whereas the other class
S. K. Das, W. S. Mohn
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Information based speaker verification
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002We discuss the conceptual and computational frameworks of information theory for decision making in speaker verification. The proposed approach departs from other conventional scoring models for speaker verification as the first approach takes into account the quantity of 'surprise' or information content. We compare the new approach with a widely used
Tuan D. Pham, Michael Wagner 0004
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Lightweight Embeddings for Speaker Verification
2018This paper presents speaker verification (SV) system using deep neural networks with hash representations (binarization) of embeddings. The training procedure is performed on NIST SRE train set, verification is performed on the same corpus with test set. The system architecture is based on deep recurrent layers with attention mechanism.
Maxim Tkachenko +3 more
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Speaker verification for multimedia application
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005In this paper the possibilities of modern speaker verification systems have been described. One of the most important tasks is a proper definition of feature vectors. The long-term spectra vector has been chosen as the background for text-independent verification system.
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Disentangled Speaker Embedding for Robust Speaker Verification
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Lu Yi 0001, Man-Wai Mak
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Data augmentation for speaker verification
Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering, 2022Shiqing Yang, Min Liu
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