参数资料
型号: AC300030
厂商: Microchip Technology
文件页数: 61/64页
文件大小: 0K
描述: KIT ACOUSTIC ACCESSORY
标准包装: 1
附件类型: 配件套件
适用于相关产品: 杂讯抑制/回声消除库
Application Programming Interface (API)
4.8
APPLICATION TIPS
Although the AEC algorithm makes a best effort to suppress the echo in a system, its
performance can be optimized by proper selection of parameters. In general,
experimentation with this library is encouraged.
Some tips for affecting the performance of the algorithm are as follows:
1. The optimum input signal levels for testing audio and communication systems
are generally considered to lie between -10 dBm0 and -30 dBm0. If digital input
speech levels have peaks that are up to three-fourths of full range, then good use
is being made of the available precision; levels higher than this carry a risk of
amplitude clipping.
2. Choose a NLP level that best fits the application. A very high NLP level not only
suppresses the residual echo, but may also reduce the speech level to some
extent.
3. The Double Talk Detection Hangover can be used to adjust the window during
which the AEC algorithm will wait before applying NLP to the send signal. If the
application is experiencing some leading edge speech clipping, then try
increasing the DTD Hangover.
4. The Adaptation Hangover can be used to adjust the window during which an
adaptation hangover update stays active. This parameter can be adjusted in
situations where the speech level is low and double talk may not be detected.
5. In cases where the near-end ambient acoustic environment is noisy (such as cell
phones and automotive hands-free units), the noise level may cause the double
talk detection to be activated, thereby inhibiting adaptation. In such cases, the
AEC algorithm can be forced to adapt all the time which may improve the overall
system performance.
6. The user application should never inhibit adaptation. This feature is only
provided for test and compliance checking purposes.
? 2004-2011 Microchip Technology Inc.
DS70134F-page 61
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