Intelligent speaker training using microphone feedback and pre-loaded templates

Abstract

A programmable speaker uses characterization data stored within the memory of the speaker and digital signal processing (DSP) to digitally perform transform functions on input audio signals to compensate for speaker related distortion and listening environment distortion. In a manufacturing environment, a non-intrusive system and method for tuning the speaker is performed by applying a reference signal and a control signal to the input of the programmable speaker. A microphone detects an audible signal corresponding to the input reference signal at the output of the speaker and feeds it back to a tester which analyzes the frequency response of the speaker by comparing the input reference signal to the audible output signal from the speaker. Depending on the results of the comparison, the tester provides to the speaker an updated digital control signal with new characterization data which is then stored in the speaker memory and used to again perform transform functions on the input reference signal. The tuning feedback cycle continues until the input reference signal and the audible output signal from the speaker exhibit the desired frequency response as determined by the tester. In a consumer environment, a microphone is positioned within selected listening environments and the tuning device is again used to update the characterization data to compensate for distortion affects detected by the microphone within the selected listening environment.