Recent developments in hearing theory have resulted in the rather general acceptance of the idea that the perception of pitch of complex sounds is the result of the psychological pattern recognition process. The pitch is supposedly mediated by the fundamental of the harmonic spectrum which fits the spectrum of the complex sound optimally. The problem of finding the pitch is then equivalent to finding the best harmonic match. Goldstein [J. Acoust. Soc. Am. 54, 1496-1516 {1973)] has described an objective procedure for finding the best fit for stimuli containing relatively few spectral components. He uses a maximum likelihood criterion. Application of this procedure to various data on the pitch of complex sounds yielded good results. This motivated our efforts to apply the pattern recognition theory of pitch to the problem of measuring pitch in speech. Although we were able to follow the main line of Goldstein's procedure, some essential changes had to be made. The most important is that in our implementation not all spectral components of the complex sound have to be classified as belonging to the harmonic pattern. We introduced a harmonics sieve to determine whether components are rejected or accepted at a candidate pitch. A simple criterion, based on the components accepted and rejected, led to the decision on which candidate pitch was to be finally selected. The performance and reliability of this psychoacoustically based pitch meter were tested in a LPC-vocoder system. There is, however, an alternative approach to the problem, which, in our belief, can be highly successful. To begin with, pitch (e.g., of speech) is a subjective quantity. Therefore one might argue that the pitch meter which operates according to the principles of the human pitch extractor (the auditory system) will attain the optimum level of performance. This is un- , 1978). We propose that (1) this theory is also applicable to the (subjective) perception of pitch in speech and (2) that the theory can be put into the form of an (objective) algorithm which will produce pitch values that have a psychophysical validity as well as practical applicability. This validity stems from the fact that the data reduction in the algorithm proposed here is based on constraints known from hearing theory, which in turn relies on psychoacoustical and physiological data.In this paper we will not go into the details of the psychoacoustics of pitch. We restrict ourselves to a description of Goldstein's theory. We shall then discuss the additional steps that are involved in its application to speech material. Finally, the resulting algorithm is presented together with some data on its performance. The algorithm will briefly be compared with existing algorithms. As an example we present results of a direct comparison with the parallel processing pitch detector (PPROC) by Gold and Rabiner (1969). By considering the central processor as a system that has to match a set of frequencies to a harmonic pattern, the relation to pattern recognition is emphasized. The patte...

The frequency selectivity of the peripheral ear (e.g., at the VIIIth nerve level) is so acute that onset and offset transients in responses to short signals produce a nonnegligible extension of the signal duration. Thus, peripheral excitation patterns produced by signals which were separated in time can overlap and thereby mask each other. We refer to this type of masking as transient masking. Published data on nonsimultaneous masking and the results of two new experiments are compared with the masking that may be expected from filter transients. It is concluded that backward masking is mainly due to interactions at the level of the filter outputs, and that in forward masking, in addition to a short-term component, a long-term component is distinguishable. The latter has an exponential decay with a time constant of approximately 75 msec, and is probably related to physiological adaptation effects.

In this article, a robust numerical solution method for one-dimensional (1-D) cochlear models in the time domain is presented. The method has been designed particularly for models with a cochlear partition having nonlinear and active mechanical properties. The model equations are discretized with respect to the spatial variable by means of the principle of Galerkin to yield a system of ordinary differential equations in the time variable. To solve this system, several numerical integration methods concerning stability and computational performance are compared. The selected algorithm is based on a variable step size fourth-order Runge-Kutta scheme; it is shown to be both more stable and much more efficient than previously published numerical solution techniques.

Measurements of psychophysical two-tone suppression in a number of subjects are described. Levels of the stimulus components (suppressee, L,, and suppressor, L2) were the primary experimental variables. In all experiments the pulsation threshold was used with the probe frequency fe fixed at the suppressee frequency f,. In an initial experiment fl was fixed at 1 kHz. The suppressor frequency f2 ranged from 0.2 to 1.4 kHz. At appropriate levels all subjects showed significant suppression. Suppression was found to decrease to zero as f2 approached fl-The amount of suppression depended on both L• and L2 in a way not accounted for by any of the current theories of two-tone suppression. At higher overall levels suppression became increasingly prominent. The amount of two-tone suppression in a given stimulus condition depended strongly on the subject. The maximu•n amount of suppression measured was about 35 dB. In a second experiment it was verified that suppression follows the same pattern at other frequencies f• (0.5, 2, and 4 kHz). Data for equal f2/f• ratios were quite similar. The two-tone suppression effect decreased in a noisy environment. Within a 20-dB range of signal-to-noise ratios the effect of noise changed from negligible to the virtually complete elimination of two-tone suppression.

This paper concerns the problem of correcting spin-history artefacts in fMRI data. We focus on the influence of through-plane motion on the history of magnetization. A change in object position will disrupt the tissue's steady-state magnetization. The disruption will propagate to the next few acquired volumes until a new steady state is reached. In this paper we present a simulation of spin-history effects, experimental data, and an automatic two-step algorithm for detecting and correcting spin-history artefacts. The algorithm determines the steady-state distribution of all voxels in a given slice and indicates which voxels need a spin-history correction. The spin-history correction is meant to be applied before standard realignment procedures. To obtain experimental data a special phantom and an MRI compatible motion system were designed. The effect of motion on spin-history is presented for data obtained using this phantom inside a 1.5-T MRI scanner. We show that the presented algorithm is capable of detecting the occurrence of a displacement, and it determines which voxels need a spin-history correction. The results of the phantom study show good agreement with the simulations.