Download Human Perception and Computer Extraction of Musical Beat Strength
Musical signals exhibit periodic temporal structure that create the sensation of rhythm. In order to model, analyze, and retrieve musical signals it is important to automatically extract rhythmic information. To somewhat simplify the problem, automatic algorithms typically only extract information about the main beat of the signal which can be loosely defined as the regular periodic sequence of pulses corresponding to where a human would tap his foot while listening to the music. In these algorithms, the beat is characterized by its frequency (tempo), phase (accent locations) and a confidence measure about its detection. The main focus of this paper is the concept of Beat Strength, which will be loosely defined as one rhythmic characteristic that could allow to discriminate between two pieces of music having the same tempo. Using this definition, we might say that a piece of Hard Rock has a higher beat strength than a piece of Classical Music at the same tempo. Characteristics related to Beat Strength have been implicitely used in automatic beat detection algorithms and shown to be as important as tempo information for music classification and retrieval. In the work presented in this paper, a user study exploring the perception of Beat Strength was conducted and the results were used to calibrate and explore automatic Beat Strength measures based on the calculation of Beat Histograms.
Download Circle Maps as a Simple Oscillators for Complex Behavior: II. Experiments
The circle map is a general non-linear iterated function that maps the circle onto itself. In its standard form it can be interpreted as a simple sinusoidal oscillator which is perturbed by a non-linear term. By varying the strength of the non-linear contribution a rich array of non-linear responses can be achieved, including waveshaping, pitch-bending, period-doubling and highly irregular patterns. We describe a number of such examples and discuss their subjective auditory perception.
Download Exploring the Sound of Chaotic Oscillators via Parameter Spaces
Chaotic oscillators are exciting sources for sound production due to their simplicity in implementation combined with their rich sonic output. However, the richness comes with difficulty of control, which is paramount to both their detailed understanding and in live musical performance. In this paper, we propose perceptually motivated parameter planes as a framework for studying the behavior of chaotic oscillators for musical use. Motivated by analysis via winding numbers, we extend traditional study of chaotic oscillators by using local features that are perceptually inspired. We illustrate the framework on the example of variations of the circle map. However, the framework is applicable for a wide range of sound synthesis algorithms with nontrivial parametric mappings.
Download Topologizing Sound Synthesis via Sheaves
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.