Fast fundamental frequency determination via adaptive autocorrelation
Michael Staudacher, Viktor Steixner, Andreas Griessner, Clemens Zierhofer · EURASIP Journal on Audio Speech and Music Processing · 2016
We present an algorithm for the estimation of fundamental frequencies in voiced audio signals. The method is based on an autocorrelation of a signal with a segment of the same signal. During operation, frequency estimates are calculated and the segment is updated whenever a period of the signal is detected. The fast estimation of fundamental frequencies with low error rate and simple implementation is interesting for real-time speech signal processing.