This paper describes a new efficient and sample based monophonic pitch tracking approach using multiple phase locked loops (PLLs). Hereby, distinct subband signals traverse pairs of individually parameterized PLLs. Based on the relation of the instantaneous pitch sample of respective PLLs to one another, relevant features per pitch candidate are derived. These features are combined into pitch candidate scores. Pitch candidates which exhibit the maximum score per sampling instance and exceed a voicing threshold, contribute to the overall pitch track. Evaluations with up to date datasets show that the tracking performance, compared to implementations which use only one PLL has significantly improved and nearly approaches the scores of a state of the art monophonic pitch tracker.

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In the digital simulation of non-linear audio effect circuits, the arising non-linear equation system generally poses the main challenge for a computationally cheap implementation. As the computational complexity grows super-linearly with the number of equations, it is beneficial to decompose the equation system into several smaller systems, if possible. In this paper we therefore develop an approach to determine such a decomposition automatically. We limit ourselves to cases where an exact decomposition is possible, however, and do not consider approximate decompositions.

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In this work, analog guitar amplifiers are modeled with an automated procedure using iterative optimization techniques. The digital model is divided into functional blocks, consisting of lineartime-invariant (LTI) filters and nonlinear blocks with nonlinear mapping functions and memory. The model is adapted in several steps. First the filters are measured and afterwards the parameters of the digital model are adapted for different input signals to minimize the error between itself and the analog reference system. This is done for a small number of analog reference devices. Afterwards the adapted model is evaluated with objective scores and a listening test is performed to rate the quality of the adapted models.

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Using bandlimited impulse train (BLIT) synthesis, it is possible to generate waveforms with a configurable number of harmonics with an equal amplitude. In contrast to the sinc-pulse, which is typically used for bandlimiting in BLIT and only allows to set the cutoff frequency, a Hammerich pulse can be tuned by two independent parameters for cutoff frequency and stop band roll-off. Replacing the perfect lowpass sinc-pulse in BLIT with a Hammerich pulse, it is possible to directly synthesise a multitude of signals with an adjustable lowpass spectrum.

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In this paper a study on the performance of the short time autocorrelation function for the determination of correct pitch candidates for non-stationary sounds is presented. Input segments of a music or speech signal are analyzed by extracting the autocorrelation function and a weighting function is used to weight candidates for assessing their harmonic strength. Furthermore, a decision is devised which alerts if there are possible non-related jumps on the fundamental frequency track. A technique to modify the spectral content of the signal is presented to compensate for these jumps, and a heuristic to return a steady fundamental frequency track for monophonic recordings is presented. The system is evaluated with several databases and with other algorithms. Using the compensation algorithm increases the performance of the ACF and outperforms current detection algorithms.

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Peak and shelving filters are parametric infinite impulse response filters which are used for amplifying or attenuating a certain frequency band. Shelving filters are parametrized by their cut-off frequency and gain, and peak filters by center frequency, bandwidth and gain. Such filters can be cascaded in order to perform audio processing tasks like equalization, spectral shaping and modelling of complex transfer functions. Such a filter cascade allows independent optimization of the mentioned parameters of each filter. For this purpose, a novel approach is proposed for deriving the necessary local gradients with respect to the control parameters and for applying the instantaneous backpropagation algorithm to deduce the gradient flow through a cascaded structure. Additionally, the performance of such a filter cascade adapted with the proposed method, is exhibited for head-related transfer function modelling, as an example application.

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