Download The Wablet: Scanned Synthesis on a Multi-Touch Interface This paper presents research into scanned synthesis on a multitouch screen device. This synthesis technique involves scanning a wavetable that is dynamically evolving in the manner of a massspring network. It is argued that scanned synthesis can provide a good solution to some of the issues in digital musical instrument design, and is particularly well suited to multi-touch screens. In this implementation, vibrating mass-spring networks with a variety of configurations can be created. These can be manipulated by touching, dragging and altering the orientation of the tablet. Arbitrary scanning paths can be drawn onto the structure. Several extensions to the original scanned synthesis technique are proposed, most important of which for multi-touch implementations is the freedom of the masses to move in two dimensions. An analysis of the scanned output in the case of a 1D ideal string model is given, and scanned synthesis is also discussed as being a generalisation of a number of other synthesis methods.
Download Digitally Moving An Electric Guitar Pickup This paper describes a technique to transform the sound of an arbitrarily selected magnetic pickup into another pickup selection on the same electric guitar. This is a first step towards replicating an arbitrary electric guitar timbre in an audio recording using the signal from another guitar as input. We record 1458 individual notes from the pickups of a single guitar, varying the string, fret, plucking position, and dynamics of the tones in order to create a controlled dataset for training and testing our approach. Given an input signal and a target signal, a least squares estimator is used to obtain the coefficients of a finite impulse response (FIR) filter to match the desired magnetic pickup position. We use spectral difference to measure the error of the emulation, and test the effects of independent variables fret, dynamics, plucking position and repetition on the accuracy. A small reduction in accuracy was observed for different repetitions; moderate errors arose when the playing style (plucking position and dynamics) were varied; and there were large differences between output and target when the training and test data comprised different notes (fret positions). We explain results in terms of the acoustics of the vibrating strings.
Download A Comparison of Extended Source-Filter Models for Musical Signal Reconstruction Recently, we have witnessed an increasing use of the sourcefilter model in music analysis, which is achieved by integrating the source filter model into a non-negative matrix factorisation (NMF) framework or statistical models. The combination of the source-filter model and NMF framework reduces the number of free parameters needed and makes the model more flexible to extend. This paper compares four extended source-filter models: the source-filter-decay (SFD) model, the NMF with timefrequency activations (NMF-ARMA) model, the multi-excitation (ME) model and the source-filter model based on β-divergence (SFbeta model). The first two models represent the time-varying spectra by adding a loss filter and a time-varying filter, respectively. The latter two are extended by using multiple excitations and including a scale factor, respectively. The models are tested using sounds of 15 instruments from the RWC Music Database. Performance is evaluated based on the relative reconstruction error. The results show that the NMF-ARMA model outperforms other models, but uses the largest set of parameters.
Download Onset Detection Revisited Various methods have been proposed for detecting the onset times of musical notes in audio signals. We examine recent work on onset detection using spectral features such as the magnitude, phase and complex domain representations, and propose improvements to these methods: a weighted phase deviation function and a halfwave rectified complex difference. These new algorithms are compared with several state-of-the-art algorithms from the literature, and these are tested using a standard data set of short excerpts from a range of instruments (1060 onsets), plus a much larger data set of piano music (106054 onsets). Some of the results contradict previously published results and suggest that a similarly high level of performance can be obtained with a magnitude-based (spectral flux), a phase-based (weighted phase deviation) or a complex domain (complex difference) onset detection function.