When listening to music, humans often focus on melodic and rhythmic elements to identify specific songs or genres. While these representations may be quite simple, they still capture and differentiate higher level aspects of music such as expressive intent and musical style. In this work we seek to extract and represent rhythmic patterns from a polyphonic corpus of audio encompassing a number of styles. A compact feature is designed that probabilistically models rhythmic activations within musical beat divisions through histograms of Inter-Onset-Intervals (IOI). Onset detection functions are calculated from multiple frequency bands of a perceptually motivated filter bank. This allows for patterns of lower pitched and higher pitched onsets to be described separately. Through a set of supervised and unsupervised experiments, we show that this feature is well suited for a variety of tasks in which quantifying rhythmic style is necessary.

Access to hardware and software tools for producing music has become commonplace in the digital landscape. While the means to produce music have become widely available, significant time must be invested to attain professional results. Mixing multi-channel audio requires techniques and training far beyond the knowledge of the average music software user. Achieving balance and clarity in a mixture comprising a multitude of instrument layers requires experience in evaluating and modifying the individual elements and their sum. Creating a mix involves many technical concerns (level balancing, dynamic range control, stereo panning, spectral balance) as well as artistic decisions (modulation effects, distortion effects, side-chaining, etc.). This work proposes methods to model the relationships between a set of multi-channel audio tracks based on short-time spectral-temporal characteristics and long term dynamics. The goal is to create a parameterized space based on high level perceptual cues to drive processing decisions in a multi-track audio setting.

The Adobe Flash platform has become the de facto standard for developing and deploying media rich Web applications and games. The relative ease-of-development and cross-platform architecture of Flash enables designers to rapidly prototype graphically rich interactive applications, but comprehensive support for audio and signal processing has been lacking. ActionScript, the primary development language used for Flash, is poorly suited for DSP algorithms. To address the inherent challenges in the integration of interactive audio processing into Flash-based applications, we have developed the DSP Audio Toolkit for Flash, which offers significant performance improvements over algorithms implemented in Java or ActionScript. By developing this toolkit, we hope to open up new possibilities for Flash applications and games, enabling them to utilize real-time audio processing as a means to drive gameplay and improve the experience of the end user.