Sound pressure level measurement and spectral analysis of brief acoustic transients

Electroencephalography and clinical Neurophysiology, 1984, 57:83-91 Elsevier Scientific Publishers Ireland, Ltd.

83

S O U N D P R E S S U R E LEVEL M E A S U R E M E N T AND SPECTRAL ANALYSIS O F BRIEF ACOUSTIC TRANSIENTS ROBERT BURKARD 1

Waisman Center on Human Development and Mental Retardation, and Department of Communicative Disorders, University of Wisconsin-Madison, Madison, WI 53706 (U.S.A.) (Accepted for publication: July 13, 1983)

Auditory evoked potentials (AEPs) have in recent years become standard clinical tools in the areas of audiology, otology, neurology, and pediatrics. As in any area of sensory investigation, response interpretation is critically dependent on control of stimulation parameters. Stimulus intensity influences the various components of the AEP. With increasing stimulus intensity, there is an increase in amplitude and a decrease in latency of the peaks of the brain-stem evoked response (BER) (Starr and Achor 1975; Coats et al. 1979). Thornton et al. (1977) found that with increasing tone burst intensity there was an increase in amplitude and a decrease in latency of the peaks of the middle component AEPs. There is an increase in peak identification, an increase in amplitude, and a decrease in latency of N1 and P2 of the late component AEP with increasing stimulus intensity (Rapin et al. 1966; Rose and Ruhm 1966). The AEP is dependent on stimulus frequency and envelope. Using brief tonal stimuli (tone bursts or filtered clicks), the latency of wave V of the brainstem evoked response decreases with increasing frequency (Coats et al. 1979; Picton et al. 1979; Suzuki and Horiuchi 1981). Thornton et al. (1977) found that with increasing stimulus frequency there was a decrease in the amplitude and latency of peaks Na through Nc of the middle component AEPs. The BER, middle and late components have 1 Send all correspondence to: Robert Burkard, Waisman Center on Human Development and Mental Retardation, 1500 Highland Avenue, University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

been classified as onset potentials (Davis 1976). Onset potentials respond to stimulus presentation but unlike the cochlear microphonic or frequency following response, do not give a response which continues throughout the duration of the stimulus. Although these potentials are classified as onset potentials, they do exhibit some duration dependencies which are as yet only incompletely defined. Kodera et al. ( 1 9 7 9 ) r e p o r t e d that with increasing stimulus rise/fall time there was an increase in latency and a decrease in amplitude of wave V of the brain-stem evoked response, Na and Pa of the middle component AEP, and P1, N1, and P2 of the late component AEP. Hecox et al. (1976) found an increase in latency and a decrease in amplitude of wave V of the brain-stem evoked response with increasing noise burst duration, but these effects were eliminated by an increase in stimulus off time. Suzuki and Horiuchi (1981) evaluated the temporal summation of energy by wave V of the BER using a constant slope, variable duration, triangularly modulated tone burst. They found that energy was integrated over several msec, with this time period of integration inversely related to tone burst frequency. Lane et al. (1971) found an increase in middle component Nb-Pb amplitude with increasing tone burst duration from 20 to 40 msec. Onishi and Davis (1968) reported an increase in N1-P1 amplitude with an increase in stimulus duration from 3 to 30 msec. These reports demonstrate the sensitivity of these measures to stimulus intensity, frequency, and envelope and suggest the importance of the calibration of sound pressure and spectral characteristics of the acoustic stimuli used to elicit

0013-4649/84/$03.00 © 1984 Elsevier Scientific Publishers Ireland, Ltd.

84

AEPs. The stimuli used to elicit AEPs are typically brief in duration. The measurement of sound pressure and spectrum of transient stimuli is technically more difficult than the measurement of continuous stimuli. This technical note reviews methods of sound pressure and spectral measurement of brief acoustic transients, and reports the influence of selected stimulus and measurement variables on acoustic spectrum.

R. B U R K A R D

(Nicolet Med80) and monitored on an oscilloscope (Tektronix RM504). Hard copy for both time domain (Nicolet Med80) and frequency domain (Hewlett Packard 3582A) analyses were produced by X-Y plotters (Hewlett Packard 7010B).

Sound pressure measurements

Sound pressure is reported in decibels sound pressure level (dB SPL), where: Instrumentation

Clicks were 0.1 msec electrical pulses generated by an interval timer (Grass $88). Filtered clicks were produced by routing brief electrical pulses through a bandpass filter (Krohn-Hite 3343). Tone bursts were generated by routing a sinusoid (Hewlett Packard 3300A function generator) through an electronic switch (University of Wisconsin Medical Electronics) which was gated by an interval timer (Grass $88). Amplification, when required, was provided by a power amplifier (South West Technical Products 207/A). These signals were attenuated (Hewlett Packard 350D) and transduced. Unless otherwise noted, the transducer was a TDH-49 earphone mounted in an M X - 4 1 / A R cushion. Acoustic analyses were performed by coupling the earphone to a 6 ml coupler (Bruel and Kjaer type 4152 artificial ear). The 6 ml coupler is meant to represent the input impedance of the human ear. The 6 ml coupler was terminated by a pressure microphone (Bruel and Kjaer type 4144) which transduced the acoustic signal to an electrical signal. This electrical signal was routed to a measuring amplifier (Bruel and Kjaer type 2610). A variety of sound measurement systems are marketed, with the entire system often referred to as a sound level meter (SLM). For some spectral measurements, the transduced acoustic signal was bandpass filtered (Krohn-Hite 3343) prior to sound pressure determination. The electrical (AC) output of the measuring amplifier was routed to a spectrum analyzer (Hewlett Packard 3582A) to allow frequency (spectral) analyses. The time domain signal was routed from the output of the measuring amplifier to a laboratory signal averager

dB SPL = 20 log(P0/P~ , ) P0 = pressure in/~pascals; Pret = 20 #paseals. Unless otherwise indicated, it is understood that dB SPL is the root mean square (rms) value, where: 2

rms = ( ~ ( P d ) / N }

1,2

P0 = observed instantaneous pressure; N = number of observations contributing to average. For very brief or intermittent stimuli, this rms SPL provides an average sound pressure for a time period which includes both stimulus on-time and off-time. For such stimuli, this running rms average is not representative of transient sound pressure, as effective averaging time is 250 msec in the 'fast' meter mode. A more appropriate measure is peak SPL (pSPL), where: pSPL = 20 1og(Pmax/Pr~ r ) where Pm~×= maximum instantaneous pressure in /~pascals; Pret = 20 #pascals. Due to the brief periods of peak pressure for stimuli such as acoustic clicks, amplifiers are needed which can measure instantaneous pSPL and eliminate meter ballistics as a limiting factor in determining peak pressure. The measuring amplifier used (Bruel and Kjaer model 2610) has a peak detector which indicates the maximum peak pressure (for transients as brief as 50 /~sec) and holds the meter to the maximum pressure observed Until the meter is reset. Most acoustic measurement systems do not have a peak-hold capability, making determination of true pSPL impossible. An alternative measurement of click SPL is referred to as peak equivalent SPL (peSPL). The AC output of the measurement amplifier or SLM

CALIBRATION OF ACOUSTIC TRANSIENTS

a

85

I

p-p I

iY b

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C Fig. 1. A schematization of two methods of determining peSPL are shown. The acoustic wave forms were produced by routing electrical signals through a transducer (TDH-49), a 6 ml coupler (Bruel and Kjaer type 4152 artificial ear), a pressure microphone (Bruel .and Kjaer type 4144) to a precision measuring amplifier (Bruel and Kjaer type 2610)..The AC output of the measurement amplifier was digitized by a laboratory computer (Nicolet Med80). a shows the acoustic wave form of a 100 ttsec click, and the measurements involved in determining baseline-to-peak (p) and peak-to-peak (p-p) peSPL, b shows the amplitude of a sinusoid necessary to equal the baseline-to-peak (p) voltage of the click, c shows the level of a sinusoid necessary to equal the peak-to-peak (p-p) voltage of the click, peSPL of the click is determined by measuring the rms SPL of the sinusoid with the basellne-to-peak or peak-to-peak voltage equal to that of the click.

is routed to an oscilloscope. The baseline-to-peak (p) or peak-to-peak (p-p) voltage of a click is determined, as shown in Fig. la. A continuous TABLE I The peak equivalent SPL (peSPL) is shown for the octave frequencies from 500 to 8000 Hz, using both the peak-to-peak and peak measurement procedures. Frequency (Hz) dB peSPL (peak-to-peak) dB peSPL (peak) 500 1000 2000 4000 8000

97 98 97 97 98

101 101 101 101 101

sinusoid is then routed through the earphone, and its level is adjusted to equal the baseline-to-peak (Fig. lb) or peak-to-peak (Fig. lc) voltage. Finally, the rms SPL is read from the sound level meter and this nominal SPL is referred to as the click peSPL. Baseline-to-peak (peak) and peak-to-peak peSPLs are shown for a range of frequencies in Table I for a click at 70 dB above the author's threshold. The greater rms voltage required for the baseline-to-peak measures results in baseline-topeak peSPL values which are 3-4 dB greater than peak-to-peak values. Additionally, the absolute peSPL for either measurement procedure is not strongly dependent on the frequency of the

86

R. BURKARD 90

TABLE II1 The rms SPL, peak SPL, and crest factor are shown for a broad band noise, sine wave, triangular wave, and square wave.

85

Broad band noise Sine wave Triangular wave Square wave

co80

rms SPL

Peak SPL

Crest factor

95 95 95 95

108 98 100 1190

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(Hz)

Fig. 2. rms SPL as a function of click repetition rate is shown. The click is a 100 /~sec pulse transduced by a TDH-49 earphone. Click level is 104.5 dB pSPL.

sinusoid. There is currently n o s t a n d a r d i z a t i o n in the m e a s u r e m e n t of p e S P L ( b a s e l i n e - t o - p e a k or p e a k - t o - p e a k ) . Therefore, r e p o r t i n g p e S P L without a s t a t e m e n t of p r o c e d u r e m a y result in an a m b i g u ity o f 3 - 4 dB in the present example. The magnitude of dB difference for the two p r o c e d u r e s is d e p e n d e n t on the s y m m e t r y of the acoustic pulse in the time d o m a i n a n d will be d e p e n d e n t on the t y p e of pulse used to drive the t r a n s d u c e r a n d on the p a r t i c u l a r t r a n s d u c e r used. A third m e t h o d of r e p o r t i n g click SPL is to increase the repetition rate of the click a n d measure the rms SPL. D u e to the relatively long analysis time used for rms measures (250 msec for the fast meter mode), with increasing rate there will be a n integration of energy a n d therefore an increase in SPL. Fig, 2 shows rms S P L as a function of

TABLE II The dB SPL values are shown for a click of constant sound pressure using 4 different measurement procedures. dB pSPL dB PeSPL (baseline-to-peak) dB peSPL (peak-to-peak) dB SPL (1000 Hz)

104.5 101 97.5 88

click repetition rate. As expected, with increasing rate there is an increase in SPL. A c o m p a r i s o n of click SPL for the techniques described is shown in T a b l e II. Click level was held c o n s t a n t at 70 dB a b o v e the a u t h o r ' s threshold for all measures. It can be seen that b a s e l i n e - t o - p e a k a n d p e a k - t o , p e a k p e S P L values are 3.5 a n d 7 dB less than pSPL, while a click at a repetition rate of 1 0 0 0 / s e c p r o d u c e s an rms SPL which is 16.5 dB less than pSPL. The preferred SPL m e a s u r e m e n t for transient signals other than clicks is d e p e n d e n t on the specific stimulus a n d on available instrumentation. F o r gated tones (called tone bursts or tone pips), the tone can either be gated c o n t i n u o u s l y a n d the rms SPL measured, or the true p S P L value can be d e t e r m i n e d . O n e d e t e r m i n a n t of the n u m e r i c relation between these two measures is the microstructure of the acoustic stimulus. T a b l e I I I shows b o t h rms SPL a n d p S P L values for a variety of continuous signals. F o r all stimuli, the level was a d j u s t e d to 95 dB rms SPL a n d then the p S P L was measured. The difference between rms a n d p e a k values is called the crest factor, and it can be seen that the crest factor is strongly d e p e n d e n t on the mic r o s t r u c t u r e of the signal. There is some confusion over the use o f the terms s o u n d pressure level (SPL), hearing level ( H L ) , and sensation level (SL). As reviewed above, dB SPL is a physical measure, referenced to 20 /~pascals. dB H L is a reference level relative to a n o r m a t i v e d a t a base. There are s t a n d a r d s (American N a t i o n a l S t a n d a r d s Institute 1970) for the dB SPL which c o r r e s p o n d to 0 dB H L (average normal threshold) o f long d u r a t i o n tones for the octave (and certain half-octave) frequencies between 125 a n d 8000 H z for clinical audiometers. There are c u r r e n t l y no s t a n d a r d s for click or tone burst

CALIBRATIONOF ACOUSTICTRANSIENTS

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, .~ 8 l'0 12 FREQUENCY (kHz) Fig. 3. Acoustic spectra of 100 /~sec clicks at 104.5 dB pSPL, determined by the use of a variable cutoff 8-pole(48 dB/octave) bandpass filter (Krohn-Hite 3343). The upper curves show absolute pSPL for constant bandwidth (200 Hz) and 1/3 octave filters. The lower curves show the corresponding spectrum level of the upper curves. Spectrum level is obtained by subtracting 10 log(bandwidth) from the observed pSPL.

30

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SPL for normative threshold. Most clinics and laboratories generate their own norms for the specific stimuli used by obtaining a mean threshold for a jury of normal hearing adults. These in-house 80

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Fig. 4. Acoustic spectra of 100 /tsec clicks through several transducers. The AC output of the measuring amplifier was input to the digital spectrum analyzer(Hewlett Packard 3582A). A Flat Top passband was used and 32 responses were summed to produce each spectrum.

norms are necessary because normative threshold is dependent on the temporal and spectral characteristics of the stimuli, and high ambient noise levels in the testing environment can elevate perceptual thresholds. There are no recognized standards for the click pSPL corresponding to normative threshold, nor is there agreement in the envelope or SPL for normative threshold of brief tonal (tone burst) stimuli. In-house values for normative threshold values are often referred to as 0 dB HL. Because these normative values are not recognized standards, it is suggested that the term dB normal H L (dB nHL) be used (Picton et al. 1977). Finally, the term dB SL refers to the level above an individual's threshold. For example, for a patient with a click threshold of 30 dB nHL, a 60 dB n H L click is 30 dB SL.

Acoustic spectrum of dicks The acoustic spectrum of a stimulus shows relative energy as a function of frequency. There are two methods of determining the acoustic spectrum of a stimulus. First, one can vary the cutoff frequency of a bandpass filter, where the upper cutoff frequency of one band abutts the lower cutoff frequency of the adjacent band. The SPL for each band in the frequency range of interest is then recorded. Second, the AC output of the SLM is digitized, and a Fourier analysis of the digitized time domain signal is performed. The Fourier transform changes a time domain signal to the frequency domain. An acoustic click is produced by ringing an earphone with a brief electrical pulse. The acoustic spectrum of a click is dependent on the duration of the electrical pulse, the transfer function of the transducer, and the dimensions of the acoustic coupler. The electrical pulse is shaped by the transfer function (filtering characteristics) of the transducer, which is further shaped by the resonant properties of the acoustic coupler. All of these influences are manifested in the acoustic spectrum. Fig. 3 shows the spectra of 100 #sec clicks through a TDH-49 earphone. The upper two curves show the absolute pSPL as measured through a variable cutoff analog filter, comparing

88

R. BURKARD

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Fig. 5. Acoustic spectra and corresponding time domain stimuli for filtered clicks are shown. Filtered clicks were produced b y ringing an 8-pole (48 dB/octave) bandpass filter (Krohn-Hite 3343) w i t h t h e high and low cutoffs set to the same nominal frequency. Frequencies ranged from 0.5 to 8 kHz. Spectra were produced by a digital spectrum analyzer (Hewlen Packard 3582A) using a Flat Top passband; 32 responses were summed to produce each spectrum.

the results to constant bandwidth (200 Hz) and 1 / 3 octave bandwidths. For 1 / 3 octave bandwidths, the spectrum shows a steeper low-frequency roltoff and a shallower high-frequency rolloff. This is due, in part, to the increase in bandwidth with increasing frequency for 1 / 3 octave filters. In order to compensate for this bandwidth effect, the spectrum levels of these spectra are also shown. Spectrum level of each band is obtained by subtracting 10 log(bandwidth) from the observed overall pSPL. Spectrum level produces an average

Fig. 7. Acoustic spectra and corresponding time domain stimuli for 4 kHz tone bursts with 1 msec rise/fall times and plateaus ranging from 0 to 10 msec. The digital spectrum analyzer (Hewlett Packard 3582A) used a Flat Top passband and 32 responses were summed to produce each spectrum.

SPL normalized to a bandwidth of 1 Hz. The spectrum level for the constant bandwidth function parallels that of the absolute pSPL function, but is displaced 23 dB, This 23 dB value represents 10 log(200), where 200 is the bandwidth (in Hz) for the constant bandwidth function. The 1 / 3 octave function is changed noticeably, with a flattening of the low-frequency rolloff and a steepening of the high-frequency rolloff. There is good agreement between the two spectrum level functions, with both showing a relatively flat response below 5 - 6 kHz, and rolling off quite steeply above this region.

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Fig. 6. Acoustic spectra and corresponding time domain stimuli for 0.5-8 kHz tone bursts with 2 msec rise/fall times and 1 msec plateaus. The digital spectrum analyzer (Hewlett Packard 3582A) used a Flat Top passband, with 32 responses summed to produce each spectrum.

2

4

6

8

I0

29.7 m*ec

FREQUENCY tkHz)

Fig. 8. Acoustic spectra and corresponding time domain stimuli for 4 kHz tone bursts with 2 msec plateaus and rise/fall times varying from 0 to 10 reset. The digital spectrum analyzer (Hewlett Packard 3582A) used a Flat Top passband and 32 responses were summed to produce each spectrum.

CALIBRATION OF ACOUSTIC TRANSIENTS

•F L A T

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Fig. 9. Acoustic spectra and corresponding time domain stimuli for 4 kHz tone bursts with 1 msec rise/fall times and 2 msec plateaus. Spectra were produced by a digital spectrum analyzer (Hewlett Packard 3582A), with 32 responses summed to produce each spectrum. Hanning and Flat Top passbands are shown. For each passband, a spectrum is shown for tone bursts centered in ihe analysis time window (upper spectra), and for tone bursts Which occur at the beginning of the analysis time window (lower spectra).

Fig. 4 shows acoustic spectra obtained by Fourier transform. The output of the measuring amplifier was routed to a spectrum analyzer (Hewlett Packard 3582A). These spectra are the average of 32 clicks. The upper cutoff frequency is 10 kHz, and the pressure scale is in relative dB. This figure shows the spectra of 3 earphones to 100 psec clicks. Spectra were vertically displaced to separate the functions. For the TDH-49 earphone, note the similarity to the spectra shown in Fig. 3. The TDH-39 has a bandwidth similar to that of the TDH-49, but with > 5 dB ripples in the passband (below roughly 6 kHz) and a steeper highfrequency rolloff. The Telex 1470 has a higher upper-frequency cutoff than the other phones, but again has large ripples in the passband. This figure demonstrates that the transducer is one determinant of the acoustic spectrum of a given electrical stimulus.

Acoustic spectra of band-limited stimuli The audiogram plots behavioral threshold as a function of tone frequency. The tonal stimuli are of long duration (greater than several hundred msec) and therefore are narrow in spectrum, i.e.,

they have energy limited to a very narrow region centered at the tone frequency. If interested in obtaining audiometric information by evoked potential techniques, it is desirable to use acoustic stimuli similar to those used in behavioral audiometry. Some AEPs, most notably the brain-stem evoked response, are onset potentials which respond only to the first few milliseconds of a stimulus. They show the most replicable responses to stimuli of short duration and rapid onset. However, as the duration of a tonal stimulus decreases, the bandwidth increases. Therefore, a compromise must be reached to provide a stimulus which is relatively narrow in spectrum but of sufficiently brief duration to provide a replicable response. In this section we will review various manipulations which influence the spectrum of band-limited stimuli. One method of obtaining narrow spectra stimuli is to pass a brief electrical pulse through a bandpass filter with the high and low cutoffs set to the same nominal frequency, producing a filtered click. Fig. 5 shows the acoustic spectra and oscillographs of 500, 1000, 2000, 4000, and 8000 Hz filtered clicks. In this and all subsequent figures, acoustic spectra are the average of 32 stimuli. Spectral peaks occur at the nominal cutoff frequencies. As frequency increases, the spectra become broader. The cause of this frequency dependence of bandwidth can be determined from the time domain responses. The duration of the filtered click is an inverse function of frequency. The rise/fall time (times from baseline to full amplitude) are 1.5-2 periods of the filter frequency, with a very brief, if existent, plateau. The broadening of spectra with increasing frequency is due to the inverse relation of bandwidth to duration. An alternative method of producing narrow spectra stimuli involves gating a sinusoid with an electronic switch. These stimuli are referred to as tone bursts or tone pips, and rise/fall time, plateau, and sinusoid frequency can be manipulated independently. Fig. 6 shows tone bursts with 2 msec rise/fall times and plateaus of 1 msec, with tone burst frequency varied from 500 to 8000 Hz. The constant envelope in the time domain can be seen in the right portion of the figure. The spectra are similar in shape across tone burst frequency.

90 The amplitudes of the peak in the spectra (or tone burst amplitude in the time domain) reflect the frequency response of the TDH-49 earphone used (see Figs. 3 and 4). Fig. 7 shows the effects of plateau duration on acoustic spectrum. Tone burst frequency is 4000 Hz, rise/fall time is 1 msec, and plateau varied from nominal values of 0 to 10 msec. Spectra were displaced vertically to separate the functions. Note the narrowing of spectrum with increasing plateau duration. The amplitude and spacing of the sidebands (secondary maxima) are complex functions of plateau duration. Fig. 8 shows the effects of rise/fall time on the acoustic spectra. The tone burst frequency is 4000 Hz, plateau is 2 msec, and rise/fall time varied nominally from 0 to 10 msec. Again, the spectra are displaced vertically to separate the functions. With increasing rise/fall time, there is a narrowing of the bandwidth of the primary maximum, a decrease in the frequency spacing of the sidebands, and a decrease in the relative amplitude of the sidebands. These effects are most dramatic for the increase in rise/fall time from 0 to 2 msec. It should be mentioned that as rise/fall time increases there is an increase in the total tone burst duration. Therefore, the changes in spectrum with increasing rise/fall time shown in Fig. 8 are, in part, due to (confounding) increases in total tone burst duration. One additional variable in digital spectral analysis is the shape of the passband. Each point in the digitized signal can be weighted prior to Fourier transformation. This weighting in the time domain influences the shape of the filter in the frequency domain. Fig. 9 shows acoustic spectra obtained through Flat Top and Hanning windows. Prior to Fourier transform, these windowing functions multiply each digitized point in the time domain by a variable. The value of this variable is at or near unity at the center of the time window, decreasing toward zero at the initial and terminal portions of the time window. In Fig. 9, stimuli were 4000 Hz tone bursts with 1 msec rise/fall times and 2 msec plateaus. For each passband, two conditions are shown. For one condition, the tone burst was centered in the time window. For the second condition, the spectrum analyzer was triggered at tone burst onset. For the centered tone

R. BURKARD bursts, there are some differences in the overall amplitudes for the two passbands, but their shapes are very similar. For the non-delayed tone bursts, the amplitudes are greatly reduced and the sidebands, if existent, are in the noise floor of the instrument. These alterations are due to the tapering of these passbands at the beginning and end of the time window. The preferred weighting function is dependent on the stimulus and the parameter of interest and for all passbands there is a tradeoff between precision in time (amplitude uncertainty) and precision in frequency (bandwidth). For example, the Flat Top passband provides good amplitude accuracy at the expense of increased bandwidth. The uniform passband (no weighting) has a narrower bandwidth but greater amplitude distortion. The Hanning passband (raised cosine window) provides an amplitude-uncertainty/frequency-resolution compromise. Many spectrum analyzers have only one passband (often the Hanning), and arguments over the best passband are academic. However, it should always be remembered that the obtained acoustic spectrum is the result of the electrical signal, transducer characteristics, and the windowing function of the spectrum analyzer.

Summary The sound pressure level (SPL) of an acoustic transient can be quantified in several ways. The SPL value obtained is dependent on measurement procedure, in addition to signal and transducer characteristics. The acoustic spectrum of a signal shows sound pressure as a function of frequency. The acoustic spectrum can be determined by the use of analog filtering or by Fourier transformation. A constant electrical signal can produce different acoustic spectra due to varying transfer functions across transducers. Signal center frequency, rise/fall time and plateau influence acoustic spectrum. Recording parameters, such as constant bandwidth versus logarithmic bandwidth filtering, or the time domain windowing function used prior to Fourier transformation, also influence the acoustic spectrum.

CALIBRATION OF ACOUSTIC TRANSIENTS R6sum6

Mesure du niveau de pression sonore et analyse spectrale de transitifs acoustiques brefs Le n i v e a u de p r e s s i o n d u s o n ( S P L ) d ' u n t r a n sitoire a c o u s t i q u e p e u t ~tre q u a n t i f i 6 d e diverses faqons. L a v a l e u r d u S P L o b t e n u e d 6 p e n d d u p r o c 6 d 6 de m e s u r e utilis6, e n p l u s des caract6rist i q u e s d u s t i m u l u s et d u t r a n s d u c t e u r . Le spectre a c o u s t i q u e d ' u n s t i m u l u s m o n t r e q u e la p r e s s i o n d u s o n est f o n c t i o n d e la fr6quence. Le spectre a c o u s t i q u e p e u t ~tre d 6 t e r m i n 6 p a r la m 6 t h o d e de f i l t r a t i o n a n a l o g i q u e o u p a r t r a n s f o r m a t i o n de F o u r i e r . U n s t i m u l u s 61ectrique c o n s t a n t p e u t p r o d u i r e diff6rents spectres a c o u s t i q u e s , s e l o n les f o n c t i o n s de t r a n s f e r t des t r a n s d u c t e u r s . L a fr6q u e n c e c e n t r a l e d u s t i m u l u s , le t e m p s d'6tablissem e n t et d ' e x t i n c t i o n , ainsi q u e le p l a t e a u i n f l u e n c e n t le spectre a c o u s t i q u e . Les p a r a m ~ t r e s d ' e n r e g i s t r e m e n t , tel u n filtrage /l b a n d e p a s s a n t e e o n s t a n t e o u ~ b a n d e l o g a r i t h m i q u e , o u la fen~tre d u d o m a i n e t e m p o r e l l e utilis~e a v a n t t r a n s f o r m a t i o n d e F o u r i e r , i n f l u e n c e n t 6 g a l e m e n t les spectres acoustiques. I am grateful to Kirk Hogan and Don Deegan, who read this document and provided many helpful suggestions. I thank Louise Roy for her assistance with the R6sum6.

References American National Standards Institute. Specifications for audiometers. ANSI, $3.6-1969, American National Standards Institute, New York, 1970. Coats, A., Martin, J. and Kidder, H. Normal short-latency electrophysiological filtered click responses recorded from

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