Download Musical Signal Analysis Using Fractional-Delay Inverse Comb Filters
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.
Download Simulation of piano sustain-pedal effect by parallel second-order filters
This paper presents a sustain-pedal effect simulation algorithm for piano synthesis, by using parallel second-order filters. A robust two-step filter design procedure, based on frequency-zooming ARMA modeling and least squares fit, is applied to calibrate the algorithm from impulse responses of the soundboard and the string register. The model takes into account the differences in coupling between the various strings. The algorithm can be applied to both sample-based and physics-based piano synthesizers.
Download Analysis of piano tones using an inharmonic inverse comb filter
This paper presents a filter configuration for canceling and separating partials from inharmonic piano tones. The proposed configuration is based on inverse comb filtering, in which the delay line is replaced with a high-order filter that has a proper phase response. Two filter design techniques are tested with the method: an FIR filter, which is designed using frequency sampling, and an IIR filter, which consists of a set of second-order allpass filters that match the desired group delay. It is concluded that it is possible to obtain more accurate results with the FIR filter, while the IIR filter is computationally more efficient. The paper shows that the proposed analysis method provides an effective and easy way of extracting the residual signal and selecting partials from piano tones. This method is suitable for analysis of recorded piano tones.
Download A New Reverberator based on Variable Sparsity Convolution
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.