Method for temporal interpolation of short-term spectra and its application to adaptive system identification

In this paper an extension of analysis filterbanks utilized in adaptive system identification schemes is presented. The extension operates as a postprocessing stage following conventional polyphase filterbanks or short-term Fourier transforms. The idea of the new method is to exploit the redundancy of succeeding short-term spectra for computing interpolated temporal supporting points. For its efficient implementation some approximations are performed - it can be shown that the postprocessing stage can be easily realized based on the weighted sum of subband signals. The new method allows for significant increase of the frameshift (subsampling rate), leading to a reduction of the computational complexity while keeping the convergence speed and the steady-state performance. Alternatively, the frameshift can be kept unchanged - in this case an improved steady-state convergence can be achieved. Real-time measurements performed with systems for acoustic echo cancellation have shown that significant improvements in terms of echo reduction can be achieved while increasing the amount of required memory only marginally.