Theres Life Above 20kHz
Theres Life Above 20kHz
Theres Life Above 20kHz
4 kHz Página 1 de 8
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Abstract
At least one member of each instrument family (strings, woodwinds, brass and percussion) produces energy to 40 kHz or above, and the
spectra of some instruments reach this work's measurement limit of 102.4 kHz. Harmonics of muted trumpet extend to 80 kHz; violin and
oboe, to above 40 kHz; and a cymbal crash was still strong at 100 kHz. In these particular examples, the proportion of energy above 20 kHz
is, for the muted trumpet, 2 percent; violin, 0.04 percent; oboe, 0.01 percent; and cymbals, 40 percent. Instruments surveyed are trumpet
with Harmon ("wah-wah") and straight mutes; French horn muted, unmuted and bell up; violin sul ponticello and double-stopped; oboe;
claves; triangle; a drum rimshot; crash cymbals; piano; jangling keys; and sibilant speech. A discussion of the significance of these results
describes others' work on perception of air- and bone-conducted ultrasound; and points out that even if ultrasound be taken as having no
effect on perception of live sound, yet its presence may still pose a problem to the audio equipment designer and recording engineer.
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I. Introduction
Each musical instrument family — strings, winds, brass and percussion — has at least one member which produces energy to 40 kHz or above.
Some of the spectra reach this work's measurement limit of 102.4 kHz.
Harmonics of French horn can extend to above 90 kHz; trumpet, to above 80; violin and oboe, to above 40; and a cymbal crash shows no
sign of running out of energy at 100 kHz. Also shown in this paper are samples from sibilant speech, claves, a drum rimshot, triangle, jangling
keys, and piano.
The proportion of energy above 20 kilohertz is low for most instruments; but for one trumpet sample it is 2%; for another, 0.5%; for
claves, 3.8%; for a speech sibilant, 1.7%; and for the cymbal crash, 40%. The cymbal's energy shows no sign of stopping at the measurement
limit, so its percentage may be much higher.
The spectra in this paper were found by recording each instrument's sound into a spectrum analyzer, then "prospecting" moment by
moment through the recordings. Two instruments (clarinet and vibraphone) showed no ultrasonics, and so are absent here. Other
instruments' sounds extended high up though at low energy. A few combined ultrasonic extension with power.
The mere existence of this energy is the point of this paper, and most of the discussion just explains why I think that the spectra are
correct, within the limits described below. At the end, however, I cite others' work on perception of air- and bone-conducted ultrasound, and
offer a few remarks on the possible relevance of our spectra to human perception and music recording.
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a. B&K 2639: preamp: A pure tone at 550 Hz, at a level 1 dB higher than that of the loudest musical-instrument sample.
b. B&K 2639: The same, but 1 dB lower than the softest musical sample.
c. B&K 2639 and Aco 4012 preamps: Tone cluster at 500, 1000 and 1500 Hz, 1 dB higher than the loudest musical sample.
d. B&K 2639 and Aco 4012 preamps: The same cluster, 1 dB lower than the softest musical sample.
Figures 18(a) and (b) show the performance of the B&K preamp to signals (c) and (d) respectively. The preamp is clearly free of harmonics
at both high and low levels. The small bump at 85 kHz in the low-level test is breakthrough from the switching power supply. [3] I don't know
the source of the even smaller bump at 50 kHz. Both are so small that they may be ignored, however.
The behavior of the Aco 4012 preamp was indistinguishable from the B&K 2639 at the higher level, and superior at the lower.
Note that these tests of the preamps are also tests of the H-P 3567A FFT analyzer. From the clean results, one may conclude that neither
preamps nor analyzer are creating a false appearance in any of the spectra in this paper.
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It is impossible however that these hypothetical rattles would fall precisely at frequencies that were harmonics for all the variety of
fundamental pitches shown in the various Figures, so I discount rattles as a source of spurious harmonics.
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would be necessary, since self-noise is generated electrically in the microphone, and has nothing to do with the presence or absence of the grid,
nor with the angle of a source relative to the microphone.
Since the room is quiet and the microphone, like any quarter-inch microphone, is noisy, I thought it likely that microphone noise
dominated. To check this, I compared two background measurements taken with the quarter-inch B&K 4135 microphone, one measurement
with grid on and the other with grid off. These two spectra were identical; they superimposed even when viewed using a vertical scale of only
0.6 dB per division.
If I assumed that the background were dominated by room sound, I would "correct" each trace to allow for the unflatness of its particular
microphone frequency response. The grid-on and grid-off random-incidence responses of the B&K 4135 differ by 3 dB at 30 kHz, 4 dB at 40
kHz, 1½ dB at 50 kHz and presumably by substantial amounts at higher frequencies, where the calibration of one of the curves is not known
(that is, not supplied by the manufacturer).
Since the background spectra I obtained are identical, "correcting" them based on two different curves would give different spectra for the
same acoustic background. This nonsensical result implies that the assumption was wrong and the measured background is indeed dominated
by microphone self-noise.
I conclude that microphone self-noise indeed dominates the background measurements, and therefore that they are good over the full
band without correction.
Now I consider the musical instrument spectra; for example, the upper trace in Figure 1(a). Here I take the applicable curve to be the on-axis
microphone response, since the microphones were always pointed at the instruments. While the on-axis "grid-off" curve is very flat to 100 kHz,
the "grid-on" curve deviates by as much as 6 dB, and moreover is not known beyond 70 kHz. When correcting the response of a "grid-on"
measurement, I freeze the correction at the 70 kHz level; that is, I make it constant from 70 kHz on up.
It is likely that the grid-on response continues to roll off beyond 70 kHz, and that therefore a true correction would not freeze at 70 kHz
but would continue increasing. This would raise the apparent level of the high-frequency energy. Thus, by freezing the correction, I am taking a
conservative approach.
It is even possible, contrary to my assumption of two paragraphs ago, that the on-axis curves may not be the appropriate ones to use at all.
At very high frequencies, because of the shortness of the wavelengths and the acoustic "liveness" of the room, the instrument may be picked up
more in a random-incidence fashion. If this be the case, then because the random-incidence response is down 9½ dB at 70 kHz, I should raise
the measured spectrum by 9½ dB at that frequency, and by appropriate amounts at other frequencies.
Thus, at very high frequencies the true spectra may be 10 or even 20 dB higher than the curves shown here. As I do not have facilities to
decide in which fashion the microphone is picking up the instruments, I use the on-axis curves to be conservative.
Using the "Math" facility of the H-P 3567A analyzer, all the spectra have been corrected as described here, to within ±0.5 dB.
A summary of this paper's findings. Column one refers to the figure showing the spectrum in question. Column two identifies the instrument.
Column three gives the sound pressure level measured at the microphone. Column four gives the measured frequency extension: For
instruments with harmonics, this is the highest frequency where harmonics are still present; for those without harmonics, the highest
frequency where the sound is still at least 10 dB above the background. (See text.) The last column tells what percentage of the total energy is
contained in the range between 20 kHz and the limit given in the previous column.
IX. Results
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Table I summarizes the results. Instruments with harmonics (Figures 1 to 9) are claimed to have energy to the highest frequencies where
harmonics are still visible. Those without harmonics (Figures 10 to 16) are claimed to have energy to the frequency where they are still 10 dB
above the background. These frequencies are listed in the fourth column of the table, while the last column tells what percentage of the total
energy of each sample lies below these frequencies but above 20 kHz. That is, a figure of 0.5 in the last column means that half of one percent
of the energy is above 20 kHz. As described above, every step has been taken to make these figures conservative, and the real figures may well
be substantially higher.
For the samples which include room reflections (Figures 1 to 10), I do not claim that our spectra are the "absolute" spectra that would be
found in anechoic measurement, because the spectra may have been altered by room resonances. As my point is simply the existence of the
ultrasonic energy, however, this does not matter.
Since Figures 11 to 16 exclude room reflections, their spectra should indeed be quantitatively accurate to within the few-decibel total error
of the analysis chain.
In a paper published in Science, Lenhardt et al. report that "bone-conducted ultrasonic hearing has been found capable of supporting
frequency discrimination and speech detection in normal, older hearing-impaired, and profoundly deaf human subjects." [5] They speculate
that the saccule may be involved, this being "an otolithic organ that responds to acceleration and gravity and may be responsible for
transduction of sound after destruction of the cochlea," and they further point out that the saccule has neural cross-connections with the
cochlea. [6]
Even if we assume that air-conducted ultrasound does not affect direct perception of live sound, it might still affect us indirectly through
interfering with the recording process. Every recording engineer knows that speech sibilants (Figure 10), jangling key rings (Figure 15), and
muted trumpets (Figures 1 to 3) can expose problems in recording equipment. If the problems come from energy below 20 kHz, then the
recording engineer simply needs better equipment. But if the problems prove to come from the energy beyond 20 kHz, then what's needed is
either filtering, which is difficult to carry out without sonically harmful side effects; or wider bandwidth in the entire recording chain,
including the storage medium; or a combination of the two.
On the other hand, if the assumption of the previous paragraph be wrong — if it is determined that sound components beyond 20 kHz do
matter to human musical perception and pleasure — then for highest fidelity, the option of filtering would have to be rejected, and recording
chains and storage media of wider bandwidth would be needed.
Acknowledgements
This project went from a long-held idea of mine to reality because of the enthusiasm of Scott Kelly, Sandee Perez and Hovel Babikian, students
in my Caltech course "Projects in Music & Science," EE/Mu 107. I am grateful for their substantial help in getting started.
Without the help of my friend Prof. Gerald Jay Sussman of MIT, the work would not have been finished. As a visiting faculty member at
Caltech during 1991-92, and continuing since then, he has contributed his deep knowledge, lucid teaching, and experienced counsel.
Sincere gratitude also to:
Caltech's Robert McEliece, Barry Megdal and the late Ed Posner for interest and support;
Hewlett Packard Corporate Gifts; Rick Walker (former student in EE/Mu 107) for his good offices; Mac MacDonald for patient and
knowledgeable field support; and Fred Cruger, Paul Gallagher, Norm Olsen and Bob Youden;
Aco/Pacific Co. and Noland Lewis for equipment and information;
Bruel & Kjaer Instruments, and Erling Frederiksen and Joe Chou for information;
"Anonymous," whose $10,000 gift allowed the purchase of crucial equipment;
Doug Sax, Ernst Schoenthal;
Denise Bovet, for calculations of inharmonicity of piano strings;
the late Bart Locanthi, who was generous with his interest and knowledge;
Julie Sussman, for careful reading and useful comments;
and Daniel W. Martin, editor-in-chief of the Journal of the Acoustical Society of America; Patricia M. Macdonald, executive editor of the
Audio Engineering Society Journal; and the anonymous AES reviewers; for their generous assistance and good suggestions. (This does not
imply endorsement of this paper by these individuals or by their organizations or publications.)
This paper is being published long after the work was completed because of the difficulty of creating publication-quality graphs from the
data. I spent a lot of time and money discovering half a dozen programs that would not make acceptable graphs. Finally, Caltech undergrad
Peter Oakley learned to use Matlab to do the job, and carried out the work reliably and creatively.
The Web (HTML) programming of this paper was done by David Boyk, of MegaHard Design.
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References
[1] Personal communications from Mac MacDonald and Steven Bye, Hewlett Packard: Overload in one portion of a time capture does not
corrupt analysis of other segments. (The H-P 3567A analyzer shows overload by an "OVLD" legend on the time trace and by changing the
overloaded portion to red; so it is very easy to tell whether any given segment is usable or not. A few of my captures had tiny overloaded
segments, but I did not use these for analysis.) [back]
[4] Tsutomi Oohashi, Emi Nishina, Norie Kawai, Yoshitaka Fuwamoto, Hiroshi Imai, High-Frequency Sound Above the Audible Range
Affects Brain Electric Activity and Sound Perception. Audio Engineering Society preprint No. 3207 (91st convention, New York City).
Abstract, page 2. [back]
[5] Martin L. Lenhardt, Ruth Skellett, Peter Wang, Alex M. Clarke, Human Ultrasonic Speech Perception. Science, Vol. 253, 5 July 1991, pp.
82-85. Abstract, p. 82. [back]
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