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CS6420-CS Datasheet(PDF) 22 Page - Cirrus Logic |
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CS6420-CS Datasheet(HTML) 22 Page - Cirrus Logic |
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22 / 52 page ![]() CS6420 22 DS205PP2 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 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 Σ Adaptive Filter A E D B C + - F Figure 8. Simplified Acoustic Echo Canceller Block Diagram |
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