Speaker identification through use of features selected using genetic algorithm

The authors introduce the use of a genetic algorithm in the reduction of a 24 parameter (12 LPC derived cepstral coefficients + 12 Δ-cepstral coefficients) set to a five, six, seven, eight or ten parameter set, for each speaker in text-independent speaker identification. The experimental results show that there is ~5% increase in the recognition rate when the reduced set of parameters is used.