This paper introduces hexaphonic distortion as a way of achieving harmonically rich guitar distortion while minimizing intermodulation products regardless of playing style. The simulated hexaphonic distortion effect described in this paper attempts to reproduce the characteristics of hexaphonic distortion for use with ordinary electric guitars with mono pickups. The proposed approach uses a parallel comb filter structure that separates a mono guitar signal into its harmonic components. This simulates the six individual string signals obtained from a hexaphonic pickup. Each of the signals are then individually distorted with oversampling used to avoid aliasing artifacts. Starting with the baseline of the distorted mono signal, the simulated distortion produces fewer intermodulation products with a result approaching that of hex aphonic distortion.
A central challenge for a cappella singers is to adjust their intonation and to stay in tune relative to their fellow singers. During editing of a cappella recordings, one may want to adjust local intonation of individual singers or account for global intonation drifts over time. This requires applying a time-varying pitch-shift to the audio recording, which we refer to as adaptive pitch-shifting. In this context, existing (semi-)automatic approaches are either labor-intensive or face technical and musical limitations. In this work, we present automatic methods and tools for adaptive pitch-shifting with applications to intonation adjustment in a cappella recordings. To this end, we show how to incorporate time-varying information into existing pitch-shifting algorithms that are based on resampling and time-scale modification (TSM). Furthermore, we release an open-source Python toolbox, which includes a variety of TSM algorithms and an implementation of our method. Finally, we show the potential of our tools by two case studies on global and local intonation adjustment in a cappella recordings using a publicly available multitrack dataset of amateur choral singing.
In this paper we describe similarity graphs computed from time-frequency analysis as a guide for audio playback, with the aim of extending the content of fixed recordings in creative applications. We explain the creation of the graph from the distance between spectral frames, as well as several features computed from the graph, such as methods for onset detection, beat detection, and cluster analysis. Several playback algorithms can be devised based on conditional pruning of the graph using these methods. We describe examples for looping, granulation, and automatic montage.
In this work, a number of numerical schemes are presented in the context of virtual-analog simulation. The schemes are linearly-implicit in character, and hence directly solvable without iterative methods. Schemes of increasing order of accuracy are constructed, and convergence and stability conditions are proven formally. The schemes are able to handle stiff problems very efficiently, because of their fast update, and can be run at higher sample rates to reduce aliasing. The cases of the diode clipper and ring modulator are investigated in detail, including several numerical examples.
In recent years, a range of topological methods have emerged for processing digital signals. In this paper we show how the construction of topological filters via sheaves can be used to topologize existing sound synthesis methods. I illustrate this process on two classes of synthesis approaches: (1) based on linear-time invariant digital filters and (2) based on oscillators defined on a circle. We use the computationally-friendly approach to modeling topologies via a simplicial complex, and we attach our classical synthesis methods to them via sheaves. In particular, we explore examples of simplicial topologies that mimic sampled lines and loops. Over these spaces we realize concrete examples of simple discrete harmonic oscillators (resonant filters), and simple comb filter based algorithms (such as Karplus-Strong) as well as frequency modulation.
