Wolfgang J. Hess
Inst. of Commun. Res. and Phon. IKP), Univ. of Bonn, Poppelsdorfer Allee 47, D-5300 Bonn 1, Germany
Fundamental frequency determination methods and algorithms (PDAs) can be grouped into two major classes: time-domain PDAs and short-term analysis PDAs. The short-term analysis PDAs leave the signal domain by a short-term transformation. They supply a sequence of average fundamental frequency estimates from consecutive frames. The individual algorithm is characterized by the short-term transform it applies: autocorrelation, distance functions (average magnitude difference function), least-squares method, harmonic analysis, and multiple spectral transform (cepstrum) are the most common algorithms. The time-domain methods, on the other hand, track the signal period by period. Extraction and isolation of the fundamental harmonic, and investigation of the temporal signal structure are the two extremes between which most of these PDAs are found. Special attention is given to the time-variant aspect of frequency determination and to postprocessing methods that allow fundamental frequency tracking over time. Among these, simple smoothing and list correction procedures are found that remove isolated errors as well as sophisticated schemes that apply dynamic optimization or stochastic modeling.