A new algorithm for speech fundamental frequency estimation

In this correspondence, we present a method of detecting the fundamental frequency based on the recognition of "fundamental peaks" of a low-pass filtered (f
c
= 0.7 kHz) speech signal. Average overall recognition accuracy of approximately 99 percent for the training speech sample and 97.5 percent for a test speech sample were achieved. The experimental verification of the developed FPR (fundamental peak recognition) method also included an objective comparison to Miller's data reduction method, and a "subjective" performance evaluation using the standard cepstrum method. The FPR classification scheme is computationally efficient and easily implementable with relatively slow 8-bit microprocessors.