Minimizing the effect of period determination on the computation of amplitude perturbation in voice.

Current methods of computing amplitude perturbation present in human voices depend upon being able to accurately determine fundamental period. In this paper, two methods of estimating the amplitude perturbation present in human voices, which do not depend on accurate determination of the boundaries between fundamental periods, are described. In both of these methods, amplitude perturbation is computed as the variance of an ensemble of periods calculated after these periods have been aligned in time. In one method, time alignment is accomplished using zero-phase transformation. In the second method, an unconstrained dynamic programming procedure is used. The accuracy of estimating amplitude perturbation by these two methods is evaluated using synthetic and natural voice signals and is also compared with an estimation using zero-padding based time alignment. The unconstrained dynamic programming method is shown to provide accurate estimation of voice amplitude perturbation over a variety of signal conditions.

Determination of glottal excitation cycles in running speech.

The three-channel pitch determination algorithm (PDA) presented in this paper combines a short-term analysis PDA, which derives fundamental frequency via a periodicity criterion, and two time domain PDAs that determine the instants of glottal closure according to local signal criteria. The first of these algorithms correlates the speech signal with an estimate of the impulse response of the vocal tract; the second applies a neural network. The reliability of these time domain PDAs is increased by constraints on the range of F0 imposed by the short-term analysis PDA. First results show that the algorithm can be applied to both accurate pitch period determination of running speech and voice quality measurements, particularly the measurements of voice jitter.

Algorithms and devices for pitch determination of speech signals.

In this paper the various pitch determination methods and algorithms (PDAs) are 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 pitch estimates from consecutive frames. The individual algorithm is characterized by the short-term transform it applies. 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. After the review of these principles the paper finally discusses different application-oriented aspects, i.e., the role of the PDA in phonetics, education, phoniatrics, and speech communication systems.