### ASA 124th Meeting New Orleans 1992 October

## 4pMU1. Fundamental frequency determination of speech and singing voice---A
review.

**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.