A Methodology for speaker-dependent acoustic features based on a simplified cortical response for speaker verification systems

Recently, the incorporation of the research done in biologically inspiredsystems has shown satisfactory results. A promising researcharea is the understanding of the human auditory systems and itsperformance under noisy conditions. Moreover, the incorporationof brain functions (cortical response) as an active part of the auditorysystem seems a viable alternative to increase the robustness ofspeech and speaker recognition systems. In this study, we proposea simplified model of the mammalian central auditory system forspeaker verification systems. This model is based on a dimension expansionrepresentation, attempting to capture the response of thecortical cells. Then, by means of the Principal Component Analysis(PCA) approach, we reduce the dimensionality and create speakerdependentfeatures. Our results showed that by using our modelingtechnique, we were able to improve the performance of speaker verificationsystems