Correntropy function for fundamental frequency determination of musical instrument samples
Expert Systems with Applications: An International Journal
Monaural voiced speech segregation based on dynamic harmonic function
EURASIP Journal on Audio, Speech, and Music Processing
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
The C-loss function for pattern classification
Pattern Recognition
Hi-index | 0.00 |
This paper proposes a novel pitch determination algorithm (PDA) based on the newly introduced concept of a generalized correlation function called correntropy. Correntropy is a positive definite kernel function which implicitly transforms the original signal into a high-dimensional reproducing kernel Hilbert space (RKHS) in a nonlinear way, 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 computes the summary of correntropy functions from the outputs of an equivalent rectangular bandwidth (ERB) filter bank. We present simulations on pitch determination for a single vowel, double vowels, and a benchmark database test. Simulations show that correntropy exhibits much better resolution than conventional autocorrelation in pitch determination and outperforms other PDAs in the benchmark database test.