CDB6420 Cirrus Logic Inc, CDB6420 Datasheet - Page 22
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CDB6420
Manufacturer Part Number
CDB6420
Description
Development Kit
Manufacturer
Cirrus Logic Inc
Datasheet
1.CDB6420.pdf
(52 pages)
Specifications of CDB6420
Silicon Manufacturer
Cirrus Logic
Application Sub Type
Speakerphone
Kit Application Type
Audio / Video / TV
Silicon Core Number
CS6420
Kit Contents
Board
Kit Features
Analog And Digital Patch Area
Lead Free Status / RoHS Status
Contains lead / RoHS non-compliant
DESIGN CONSIDERATIONS
When designing the CS6420 into a system, it is im-
portant to keep several considerations in mind.
These concerns can be loosely grouped into three
categories: algorithmic considerations, circuit de-
sign considerations, and system design consider-
ations.
Algorithmic Considerations
The CS6420 facilitates full-duplex hands-free
communication via many algorithms running on
the Digital Signal Processor that is the core of the
CS6420. Among these are the algorithms that per-
form the adaptive filtering, the half-duplex switch-
ing, digital volume control, and supplementary
echo suppression.
Full-Duplex Mode
Full-duplex hands-free communication is achieved
through a technique called adaptive filtering. The
basic principle behind adaptive filtering is that the
acoustic path between speaker and microphone can
be modeled by a transfer function which can be dy-
namically determined by an adaptive digital filter.
This principle assumes good update control and
speech/tone detection algorithms to prevent the fil-
ter from mistraining.
Theory of Operation
Figure 8 illustrates how the adaptive filter can can-
cel echo and reduce loop gain. The echo path of the
system is between points B and C: the speaker to
22
A
Figure 8. Simplified Acoustic Echo Canceller
E
Adaptive Filter
D
Block Diagram
F
-
+
C
B
microphone coupling. A signal injected at A
(sometimes called a “training signal”) is sent both
to B, the input of the echo path, and to F, the input
of the adaptive filter. The signal at B is modified by
the transducers and the environment, and received
at point C (an “Echo”). Meanwhile, let us assume
for argument’s sake that the adaptive filter has ex-
actly the right transfer function to match the echo
path BC, and so the signal at point D is approxi-
mately equal to the signal at point C. After these are
subtracted by the summing element, all that is left
is the error signal at point E, which should be very
small.
If a person were to speak into the microphone at
point C, that signal would pass through the sum-
ming element unchanged because the adaptive fil-
ter had no comparable input to subtract out. In this
manner, the person at A and the person at C may si-
multaneously speak and A will not hear his own
echo.
In the real world, the echo path is not static. It will
change, for example, when people move in the
room, when someone moves the speaker or the mi-
crophone, or when someone drops a piece of paper
on top of the speaker. So, the filter needs to adapt
to modify its transfer function to match that of the
environment. It does so by measuring the error sig-
nal at point E and trying to minimize it. This signal
is fed back to the adaptive filter to measure perfor-
mance and how best to adapt, or train.
The trouble arises when the person at the near-end
(C) speaks: the error signal will be non-zero, but
the adaptive filter should not change. If it tries to
train to the near-end signal, the adaptive filter has
no way to reduce the error signal, because there is
no input to the filter, and therefore no output from
it. The adaptive filter would mistrain.
To prevent this mistraining, the echo canceller uses
double-talk detection algorithms to determine
when to update. These update control algorithms
CS6420
DS205PP2