Mackie SP-DSP1 White Paper

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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.

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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

signicantly 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-specic user

parameters. Finally, while playing music, an

Auto Calibration

is initiated. It’s fast and simple!