Speaker identification and verification using Gaussian mixture speaker models
Speech Communication
AHUMADA: A large speech corpus in Spanish for speaker characterization and identification
Speech Communication - Speaker recognition and its commercial and forensic applications
ANF Stochastic Low Rate Stimulation
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Low rate stochastic strategy for cochlear implants
Neurocomputing
Assessment of a Speaker Recognition System Based on an Auditory Model and Neural Nets
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
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In the present work an assessmet of the influence of the different components that form a bioinspired auditory model in the speaker recognition performance by means of neuronal networks, at different sound pressure levels and Gaussian white noise of the voice signal, was made. The speaker voice is processed through three variants of an auditory model. From its output, a set of psychophysical parameters is extracted, with which neuronal networks for speaker recognition will be trained. Furthermore, the aim is to compare three standardization methods of parameters. As a conclusion, we can observed how psycophysical parameters characterize the speaker with acceptable rates of recognition; the typology of auditory model has influence on speaker recognition.