A novel filter configuration for the analysis of harmonic musical signals is proposed. The method is based on inverse comb filtering that allows for the extraction of selected harmonic components or the background noise component between the harmonic spectral components. A highly accurate delay required in the inverse comb filter is implemented with a high-order allpass filter. The paper shows that the filter is easy to design, efficient to implement, and it enables accurate low-level feature analysis of musical tones. We describe several case studies to demonstrate the effectiveness of the proposed approach: isolating a single partial from a synthetic signal, analyzing the even-to-odd ratio of harmonics in a clarinet tone, and extracting the residual from a bowed string tone.

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An efficient algorithm approximating the late part of room reverberation is proposed. The algorithm partitions the impulse response tail into variable-length segments and replaces them with a set of sparse FIR filters and lowpass filters, cascaded with several Schroeder allpass filters. The sparse FIR filter coefficients are selected from a velvet noise sequence, which consists of ones, minus ones, and zeros only. In this application, it is sufficient perceptually to use very sparse velvet noise sequences having only about 0.1 to 0.2% non-zero elements, with increasing sparsity along the impulse response. The algorithm yields a parametric approximation of the late part of the impulse response, which is more than 100 times more efficient computationally than the direct convolution. The computational load of the proposed algorithm is comparable to that of FFT-based partitioned convolution techniques, but with nearly half the memory usage. The main advantage of the new reverberator is the flexible parameterization.

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