John D. Lovell

Stimulus Features in Signal Detection

Short bursts of computer‐generated Gaussian noise were rated by observers for the presence or absence of a 500‐Hz signal tone burst. A multiple regression analysis found for each observer the linear combination of the energies in narrow bands around the tone frequency that best predicts his total ratings. The estimates of the regression coefficients provide graphs of the “frequency responses” of the observers. Most of the reliable variance in the total ratings was accounted for by the regression analysis in terms of energy in narrow bands. Differences among observers are explained in terms of differential weighting by observers of features labeled “tone presence,” “pitch,” and “loudness.”

Mach Bands in Hearing

Everyone believes that there must be laterally inhibitory nerve nets fed by cochlear potentials, for otherwise it is difficult to explain the extraordinary capacity of the ear in discriminating pitch. Mach bands have not been demonstrated in audition as directly and simply as in vision. We have sought to show the existence of Mach bands (“edge effects”) in direct masking. Noise bands having theoretically infinite attenuation rates outside the passband were generated by computer from 56 sinusoids spaced randomly by frequency. Monaural masked audiograms were obtained for each of four subjects at each of two noise bands (480–580 Hz and 960–1160 Hz) and sensation levels of 20, 30, 40, 50, and 60 dB. Edge effects, as measured by contours of threshold shift, were revealed for all subjects, at every loudness, and are similar for both noise bands. Sharpening is greater at the low‐frequency end of a band and grows nonlinearly with loudness, as does upward spread of masking. An account of these data can be given in...

Digital generation of acoustic stimuli

A technique for digital generation of diverse acoustic waveforms is described. The method is embodied as a complete computer program coded in Fortran. We discuss the operation, implementation, and use of the program and its ease of adaptation for use on any computer.

Digital filtering and signal processing

The design, realization, and some of the many uses of digital filters are reviewed. Computer programs coded in FORTRAN are presented for the design of lumped parameter digital and analog filter systems which are simulated on a digital computer. Explanations of the programs are accompanied by examples of their use. There is a discussion of problems arising from errors of roundoff and approximation.

Threshold Shifts at the Edge of Noise Bands

Masked thresholds were taken at frequencies between 700 and 1300 Hz. The maskers were octave‐width, bandpass, pink noises at 50‐dB sensation level, with component frequencies between 500 and 1000 Hz and between 1000 and 2000 Hz. Masing was found to be 6 to 10 dB less at the edge of the noise bands than within the bands. The critical‐band theory prediction is 3 dB less of masking. Predictions from an additive, linear model or a multiplicative, nonlinear model of auditory neural inhibitory interaction lead to different expected amounts of masking at the band edge, even though the sensation pattern in either case can be such as to produce auditory Mach bands. In particular, an increase in masking is predicted near an edge by the linear model whereas a decrease in masking is predicted by the nonlinear model. [Work supported by the U. S. Public Health Service under Grant MH‐7809.]

Contralateral and Ipsilateral Pitch Shift in the Presence of Wide‐Band White or Pink Noise

Pitch matches were made between a fixed standard tone at 100, 400, or 1600 Hz and a variable frequency tone occurring at different time periods in the right ear. A 40 dB SL wide‐band white or pink noise occurred at the same time as the standard tone in either the right or left ear. When white noise was in the right ear, the results were similar to those of previous investigations [e.g., Schubert, J. Acoust. Soc. Amer 22, 497–499 (1950)]. Shifts of 100, 400, and 1600 Hz were, respectively, about 0%, 0.8% and 1.2% of the standard frequency, and were in an upward direction. When pink noise was in the right ear, pitch shifts were more negative by about 0.5% of the standard frequency. If pink or white noise were presented in the left ear, pitch shift was of a comparable magnitude to the case of the right ear, but the shift produced by pink noise was not consistently more negative than that produced by white noise. [Work supported by the United States Public Health Service and by the Patent Fund of the Universi...

Pitch of Noise Bands Reconsidered

An explanation is given for the difficulty of Small and Daniloffs observers [“Pitch of Noise Bands,” J. Acoust. Soc. Amer. 41, 506–512 (1967)] in making octave judgments relative to the cutoff frequency of high‐pass white noise. It is suggested that pink noise is a more appropriate psychoacoustic stimuli than white noise both in this case in general.