This invention relates to audio systems, and more particularly relates to equalization of loudspeakers.
For a loudspeaker or, simply, speaker, to render high quality audio, inherent variations with frequency in the amplitude, or sound level, of the sound reproduced by the speaker for a given level of signal driving the loudspeaker must be normalized. This process is known as speaker equalization. Traditionally, the design of equalizers has been performed by an experienced technician who uses precision instruments to measure the speaker characteristics and adjusts filters as needed to equalize the speaker. In this way, the spectral performance of the loudspeaker is compensated so that for a given audio signal power level the amplitude of the resulting sound is approximately the same for all audio frequencies in the performance range of the loudspeaker. Such a procedure is manual, time-consuming and requires significant expertise but still does not necessarily yield the best equalization possible for the resources expended.
More recently, automated equalization schemes have been proposed. For example, one such proposed scheme is an automated graphic equalizer. Such an equalizer has a plurality of channels having fixed center frequencies and fixed Qs (ratio of center frequency to bandwidth of the channel) that cover the entire audio band with filters. It has been proposed to automate the equalization process with such an equalizer by using instruments to record the spectral behavior of a loudspeaker in an environment, and then, in an automated fashion apply to varying degrees such filters so as to compensate the loudspeaker performance and thus bring the resulting spectral behavior of the loudspeaker more closely to a target curve. The approach is limited in its capacity for optimization, and the equalizer is complex, making this approach impractical for widespread use in, e.g., low cost consumer audio products. Also, there is no provision for automatically refining the optimization.
Another proposed scheme proposes equalizing a sound field by automatically deriving an inverse filter that is embodied in a combination of fast Fourier transforms (FFTs) and finite impulse response (FIR) filters. The inverse filter implementation is quite complex, however, requiring considerable resources, thus making this approach impractical also for widespread use in, e.g., consumer audio products. In addition, there is no provision for re-optimization in this scheme, either.
Therefore, it would be desirable to have a method and/or apparatus for the automatic equalization of a loudspeaker that does not involve excessive complexity in implementation. It would also be desirable to have a method and/or apparatus for the automatic equalization of a loudspeaker that automatically re-optimizes the equalization. The present invention provides such a method and apparatus.
The present invention provides a method for generating digital filters for equalizing a loudspeaker. First digital data is provided, for a tolerance range for a target response curve of sound level versus frequency for the loudspeaker. Second digital data is provided, for an actual response curve of sound level versus frequency for the loudspeaker. The first digital data is compared with the second digital data and it is determined whether the actual response curve is within the tolerance range. If the actual response curve is not within the tolerance range, digital audio filters are iteratively generated, and modified data relating to the response of said loudspeaker modified by said digital audio filters is generated. The frequency, amplitude and bandwidth of the digital audio filters are automatically optimized until the modified data is within the tolerance range or a predetermined limit on the number of digital audio filters has been reached, whichever occurs first.