Speaker recognition using dynamic synapse based neural networks with wavelet preprocessing

Two problems in the field of speaker recognition are noise robustness and low inter-speaker variability. This project involved the design of a system that is capable of speaker verification on a closed set of speakers using a wavelet processing technique that allows for a speaker-dependent feature set extraction. Verification is accomplished using a dynamic synapse based neural network with noise resistance properties that is trained using a genetic algorithm technique. Using these techniques, the system was able to perform speaker verification without being adversely affected by normal levels of noise, and perform verification despite low variability between speakers