Download Optimization of Cascaded Parametric Peak and Shelving Filters With Backpropagation Algorithm 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.
Download GstPEAQ – an Open Source Implementation of the PEAQ Algorithm In 1998, the ITU published a recommendation for an algorithm for objective measurement of audio quality, aiming to predict the outcome of listening tests. Despite the age, today only one implementation of that algorithm meeting the conformance requirements exists. Additionally, two open source implementations of the basic version of the algorithm are available which, however, do not meet the conformance requirements. In this paper, yet another non-conforming open source implementation, GstPEAQ, is presented. However, it improves upon the previous ones by coming closer to conformance and being computationally more efficient. Furthermore, it implements not only the basic, but also the advanced version of the algorithm. As is also shown, despite the nonconformance, the results obtained computationally still closely resemble those of listening tests.
Download Realtime system for backing vocal harmonization A system for the synthesis of backing vocals by pitch shifting of a lead vocal signal is presented. The harmonization of the backing vocals is based on the chords which are retrieved from an accompanying instrument. The system operates completely autonomous without the need to provide the key of the performed song. This simplifies the handling of the harmonization effect. The system is designed to have realtime capability to be used as live sound effect.
Download Polyphonic Pitch Detection by Iterative Analysis of the Autocorrelation Function In this paper, a polyphonic pitch detection approach is presented, which is based on the iterative analysis of the autocorrelation function. The idea of a two-channel front-end with periodicity estimation by using the autocorrelation is inspired by an algorithm from Tolonen and Karjalainen. However, the analysis of the periodicity in the summary autocorrelation function is enhanced with a more advanced iterative peak picking and pruning procedure. The proposed algorithm is compared to other systems in an evaluation with common data sets and yields good results in the range of state of the art systems.
Download The Tonalness Spectrum: Feature-Based Estimation of Tonal Components The tonalness spectrum shows the likelihood of a spectral bin being part of a tonal or non-tonal component. It is a non-binary measure based on a set of established spectral features. An easily extensible framework for the computation, selection, and combination of features is introduced. The results are evaluated and compared in two ways. First with a data set of synthetically generated signals but also with real music signals in the context of a typical MIR application.