Journal of the Acoustical Society of America

A theory is developed for the propagation of stress waves in a porous elastic solid containing compressible viscous fluid. The emphasis of the present treatment is on materials where fluid and solid are of comparable densities as for instance in the case of water-saturated rock. The paper denoted here as Part I is restricted to the lower frequency range where the assumption of Poiseuille flow is valid. The extension to the higher frequencies will be treated in Part II. It is found that the material may be described by four nondimensional parameters and a characteristic frequency. There are two dilatational waves and one rotational wave. The physical interpretation of the result is clarified by treating first the case where the fluid is frictionless. The case of a material containing viscous fluid is then developed and discussed numerically. Phase velocity dispersion curves and attenuation coefficients for the three types of waves are plotted as a function of the frequency for various combinations of the characteristic parameters.

During the past decade a number of variations in the simple up-down procedure have been used in psychoacoustic testing. A broad class of these methods is described with due emphasis on the related problems of parameter estimation and the efficient placing of observations. The advantages of up-down methods are many, including simplicity, high efficiency, robustness, small-sample reliability, and relative freedom from restrictive assumptions. Several applications of these procedures in psychoacoustics are described, including examples where conventional techniques are inapplicable.

This paper describes a number of objective experiments on recognition, concerning particularly the relation between the messages received by the two ears. Rather than use steady tones or clicks (frequency or time-point signals) continuous speech is used, and the results interpreted in the main statistically.

Two types of test are reported: (a) the behavior of a listener when presented with two speech signals simultaneously (statistical filtering problem) and (b) behavior when different speech signals are presented to his two ears.

Relationships between a listener's identification of a spoken vowel and its properties as revealed from acoustic measurement of its sound wave have been a subject of study by many investigators. Both the utterance and the identification of a vowel depend upon the language and dialectal backgrounds and the vocal and auditory characteristics of the individuals concerned. The purpose of this paper is to discuss some of the control methods that have been used in the evaluation of these effects in a vowel study program at Bell Telephone Laboratories. The plan of the study, calibration of recording and measuring equipment, and methods for checking the performance of both speakers and listeners are described. The methods are illustrated from results of tests involving some 76 speakers and 70 listeners.

A new auditory phenomenon has been identified in the acoustic impulse response of the human ear. Using a signal averaging technique, a study has been made of the response of the closed external acoustic meatus to acoustic impulses near to the threshold of audibility. Particular attention has been paid to the waveform of the response at post excitation times in excess of 5 ms. No previous worker appears to have extended observations into this region. The response observed after about 5 ms is not a simple extension of the initial response attributable to the middle ear. The oscillatory response decay time constant was found to change from approximately 1 ms to over 12 ms at about this time. The slowly decaying response conponent was present in all normal ears tested, but was not present in ears with cochlear deafness. This component of the response appears to have its origin in some nonlinear mechanism probably located in the cochlea, responding mechanically to auditory stimulation, and dependent upon the normal functioning of the cochlea transduction process. A cochlear reflection hypothesis received some support from these results.

A large set of sentence materials, chosen for their uniformity in length and representation of natural speech, has been developed for the measurement of sentence speech reception thresholds (sSRTs). The mean-squared level of each digitally recorded sentence was adjusted to equate intelligibility when presented in spectrally matched noise to normal-hearing listeners. These materials were cast into 25 phonemically balanced lists of ten sentences for adaptive measurement of sentence sSRTs. The 95% confidence interval for these measurements is ±2.98 dB for sSRTs in quiet and ±2.41 dB for sSRTs in noise, as defined by the variability of repeated measures with different lists. Average sSRTs in quiet were 23.91 dB(A). Average sSRTs in 72 dB(A) noise were 69.08 dB(A), or −2.92 dB signal/noise ratio. Low-pass filtering increased sSRTs slightly in quiet and noise as the 4- and 8-kHz octave bands were eliminated. Much larger increases in SRT occurred when the 2-kHz octave band was eliminated, and bandwidth dropped below 2.5 kHz. Reliability was not degraded substantially until bandwidth dropped below 2.5 kHz. The statistical reliability and efficiency of the test suit it to practical applications in which measures of speech intelligibility are required.

The purpose of this study was to replicate and extend the classic study of vowel acoustics by Peterson and Barney (PB) [J. Acoust. Soc. Am. 24, 175–184 (1952)]. Recordings were made of 45 men, 48 women, and 46 children producing the vowels /i,i,e,ε,æ,a,open‘‘oh’’,o,u,u,Λ,hook backward‘‘eh’’/ in h–V–d syllables. Formant contours for F1–F4 were measured from LPC spectra using a custom interactive editing tool. For comparison with the PB data, formant patterns were sampled at a time that was judged by visual inspection to be maximally steady. Analysis of the formant data shows numerous differences between the present data and those of PB, both in terms of average frequencies of F1 and F2, and the degree of overlap among adjacent vowels. As with the original study, listening tests showed that the signals were nearly always identified as the vowel intended by the talker. Discriminant analysis showed that the vowels were more poorly separated than the PB data based on a static sample of the formant pattern. However, the vowels can be separated with a high degree of accuracy if duration and spectral change information is included.

Sixteen English consonants were spoken over voice communication systems with frequency distortion and with random masking noise. The listeners were forced to guess at every sound and a count was made of all the different errors that resulted when one sound was confused with another. With noise or low-pass filtering the confusions fall into consistent patterns, but with high-pass filtering the errors are scattered quite randomly. An articulatory analysis of these 16 consonants provides a system of five articulatory features or “dimensions” that serve to characterize and distinguish the different phonemes: voicing, nasality, affrication, duration, and place of articulation. The data indicate that voicing and nasality are little affected and that place is severely affected by low-pass and noisy systems. The indications are that the perception of any one of these five features is relatively independent of the perception of the others, so that it is as if five separate, simple channels were involved rather than a single complex channel.

Accurate cochlear frequency-position functions based on physiological data would facilitate the interpretation of physiological and psychoacoustic data within and across species. Such functions might aid in developing cochlear models, and cochlear coordinates could provide potentially useful spectral transforms of speech and other acoustic signals. In 1961, an almost-exponential function was developed (Greenwood, 1961b, 1974) by integrating an exponential function fitted to a subset of frequency resolution-integration estimates (critical bandwidths). The resulting frequency-position function was found to fit cochlear observations on human cadaver ears quite well and, with changes of constants, those on elephant, cow, guinea pig, rat, mouse, and chicken (Békésy, 1960), as well as in vivo (behavioral–anatomical) data on cats (Schucknecht, 1953). Since 1961, new mechanical and other physiological data have appeared on the human, cat, guinea pig, chinchilla, monkey, and gerbil. It is shown here that the newer extended data on human cadaver ears and from living animal preparations are quite well fit by the same basic function. The function essentially requires only empirical adjustment of a single parameter to set an upper frequency limit, while a ‘‘slope’’ parameter can be left constant if cochlear partition length is normalized to 1 or scaled if distance is specified in physical units. Constancy of slope and form in dead and living ears and across species increases the probability that the function fitting human cadaver data may apply as well to the living human ear. This prospect increases the function’s value in plotting auditory data and in modeling concerned with speech and other bioacoustic signals, since it fits the available physiological data well and, consequently (if those data are correct), remains independent of, and an appropriate means to examine, psychoacoustic data and assumptions.

An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated over a database of speech recorded together with a laryngograph signal. There is no upper limit on the frequency search range, so the algorithm is suited for high-pitched voices and music. The algorithm is relatively simple and may be implemented efficiently and with low latency, and it involves few parameters that must be tuned. It is based on a signal model (periodic signal) that may be extended in several ways to handle various forms of aperiodicity that occur in particular applications. Finally, interesting parallels may be drawn with models of auditory processing.