A hands-free telephone or full-duplex intercom system has a feedback or echo problem because the output from the loudspeaker feeds into the microphone.
We Use Acoustic Echo Cancellation. This is realized with an adaptive or learning filter. First the filter learns from given microphone and speaker signals the acoustics. After learning, the filter can calculate an estimated microphone signal from the loudspeaker signal. This estimated mic signal is subtracted from the real mic signal. The difference signal no longer contains the loudspeaker signal - the feedback loop is broken.
The Normalized LMS has a constant convergence rate for loud and weak signals, the convergence rate controlling parameter is derived from the signal energy. For white noise signal, where all frequencies have the same energy, the NLMS performs good. But the human speech has more energy in low frequencies then in high frequencies. Therefore, a NLMS gives good echo cancellation for speech frequencies .The NLMS family is known to give good echo cancellation for moderate processing resources. This algorithm is of complexity O (3*L) with L number of taps in the NLMS filter.
1 comment:
While designing an Echo cancellation system , we have to keep two things in mind. those are:-
first recognizing the originally transmitted signal that re-appears, with some delay, in the transmitted or received signal.
secondly you have to choose the best method for designing that .some of methods are echo suppressors or echo cancellers.
To implement the system we generally use the digital signal processor technique.
You have a great idea regarding echo cancellation .
Post a Comment