A Novel Pitch Determination Algorithm based on Generalized Correlation Function
In this paper, we propose a novel pitch determination algorithm (PDA) based on the newly introduced concept of the generalized correlation function called correntropy [1]. Correntropy contains a positive definite kernel function which nonlinearly transforms the original signal into a high dimensional reproducing kernel Hilbert space (RKHS), and calculates very efficiently the generalized correlation in that RKHS. By incorporating the kernel function, correntropy is able to utilize higher order statistics to enhance the resolution of pitch estimation. The proposed PDA calculates the summary of correntropy functions from the outputs of an equivalent rectangular bandwidth (ERB) filter bank. We present simulations on pitch determination for single vowel and double vowels cases. Simulations show that correntropy exhibits much better resolution than the conventional autocorrelation method for pitch determination.