Fundamentals of speech recognition
Fundamentals of speech recognition
Speech and Audio Signal Processing: Processing and Perception of Speech and Music
Speech and Audio Signal Processing: Processing and Perception of Speech and Music
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Perceptive, non-linear speech processing and spiking neural networks
Nonlinear Speech Modeling and Applications
Unsupervised clustering with spiking neurons by sparse temporal coding and multilayer RBF networks
IEEE Transactions on Neural Networks
Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition
Neural Information Processing
Natural Computing: an international journal
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This paper presents a novel system that performs text-independent speaker authentication using new spiking neural network (SNN) architectures. Each speaker is represented by a set of prototype vectors that is trained with standard Hebbian rule and winner-takes-all approach. For every speaker there is a separated spiking network that computes normalized similarity scores of MFCC (Mel Frequency Cepstrum Coefficients) features considering speaker and background models. Experiments with the VidTimit dataset show similar performance of the system when compared with a benchmark method based on vector quantization. As the main property, the system enables optimization in terms of performance, speed and energy efficiency. A procedure to create/merge neurons is also presented, which enables adaptive and on-line training in an evolvable way.