1
Mackie Industrial White Paper
September 2000
Noise Sensing Using a Variation of the
nLMS Adaptive Filter with Auto Calibration
CHRIS JUBIEN, AES Member, COSTA LAKOUMENTAS, AES Member,
BRIAN RODEN, AES Member, DALE SHPAK, AES Member,
JEFF SONDERMEYER, AES Member
Mackie Designs, Woodinville, WA
This White Paper discusses a system that will compensate for the noise level in a room by
measuring the program and noise level sensed through an ambient microphone. The system
then changes the program level in proportion to the noise level that was sensed through the
microphone. The technique that is presented here uses a combination of analog to digital
conversion (ADC), adaptive digital ltering running on a digital signal processor (DSP), and
digital to analog conversion (DAC). The adaptive lter employed is a variation on the Normal-
ized Least Mean Squares (nLMS) method. This approach effectively “nulls out” any music
that was sensed at the ambient microphone after which the only thing that remains is the noise.
A Root Mean Square (RMS) measure of this noise level provides the ability to adjust the pro-
gram level accordingly.
0 Introduction
Virtually anyone who has ever listened to music in an auto-
mobile has realized this fundamental fact: while driving, the
music level must be louder than while the car is parked. The
reason for this is because while driving the noise level (wind,
road, etc.) is louder than while parked. This requires that the
listener constantly adjust the music level to compensate for the
varying noise levels. This is not only a problem for automo-
biles but virtually all sound systems where background noise
is varying substantially. For example: in a factory setting,
the music would be set to one level while the machinery is
running and another while it is not running. For most systems,
this requires that someone always adjust the level in propor-
tion to the noise. The question naturally arises: “why can’t
this be done automatically?” Mackie Designs has invested
a considerable amount of time in research and development
to nd an answer to this very question. In the process, we
have developed a sophisticated DSP noise sensing algorithm
that will perform this task precisely. Mackie’s SP-DSP1™
is an automatic level controller that maximizes intelligibility
by changing gain in proportion to environmental noise level
changes [6]. Basically, this system senses the level of the
ambient noise of a room and adjusts the system gain accord-
ingly. To work properly, the controller must “null out” any
effect that the program material (music) has on the noise being
received by the ambient microphone. The method we have
employed to differentiate the noise from the program material
is what makes our algorithm unique (patent pending). One
innovative feature of our algorithm is that it adapts over time
to the varying room acoustics (i.e. people, drapes, sliding
doors, etc.) to provide the best possible music rejection. This
signicantly reduces the possibility of “runaway” gain as
exhibited in existing hardware-based implementations [10].
To accomplish this, we have utilized a combination of digital
hardware (SP-DSP1™) running a complex software algorithm
[8]. Figure 0 shows the hardware block diagram of the noise
sensor. The software is actually twofold: an embedded soft-
ware algorithm plus application software (SP-Control™ for
the Palm™) to allow for ease of user control. Additionally,
the SP-DSP1™ algorithm allows for a high level of automation,
which in-turn, makes this system extremely easy to setup
and use. Unlike some of the earlier attempts at “noise sensing”,
the SP-Control™ software requires no complex procedures
during setup and calibration. The user simply places his speaker(s)
as needed and positions the ambient microphone so that it is
listening to the primary noise source. Then the appropriate
gain structure is setup as well as a few room-specic user
parameters. Finally, while playing music, an
Auto Calibration
is initiated. It’s fast and simple!
