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transparent or not) among its own building blocks. Instead of the original discrete sound(s), we get a sound that exists between sounds, or as a cloud of sounds, or as a stitching together of sounds. This way, the formal progression of a piece could be defined by the changing relationships within aurally sounds (instead of some larger-scale inter-sound relationship). For example, in one of my previous compositions, (Hard Square, for percussion quartet) I wanted an aural progression between digital music means (i.e. hardware, represented aurally at the start of the piece as a bank of the clicks individual glitches of failing hard drives) and results (i.e. simple synthesis, represented aurally at the climax of the piece as a bank of GameBoy synth and Each section of the piece therefore became a step from the former to the latter, by using the FFT tasks to create banks of sounds that exist between the origin and the destination. samples). new library was written in Java; while serious signal processing coders would not use Java for such a task, as it is slower and more computationally expensive than lower-level languages, it suited my own objectives for several reasons. First, the code was more broadly distributable This reusable between users and hardware platforms; second, it was easier to build a graphical user interface (GUI) with pre-existing Java libraries; finally, and facilitated simple transfer towards real-time usage (specifically within Max's [mxj~] Java wrapper). It contains the core classes: -PolarPhasor: holds the magnitude and phase of a single phasor. it 7
holds single frame of analysis data, consisting of an array of PolarPhasor(s). -FFTFile: holds the analysis data for a whole sound file, consisting of an array of FFTFrame(s). -FFTFrame: few utility classes for reading audio files and storing FFT settings. The signal analysis/resynthesis tasks I designed based on these classes are: -Morph: chart a line that represents morphing between two sound files -A time. -Splice: take several sound files and cut between them at moments of over similarity. -Reconstitute: take an audio file, and resynthesize it completely out of spectrally similar fragments of other audio files. spectral still use these three features in most of my work. Within Cardinality Aleph Two and American Engineer, however, I only use them in the latter, and then only the Splice and Reconstitute tasks. Therefore I omit the technical background of Morph in this text. See Figure 1 for images of the user interfaces I these tasks. for Reconstitute The reconstitution algorithm takes one file (labeled the ‘trigger’ sound), and a list of one or more files (the ‘bank’). The process takes each small segment of the trigger sound, compares it against all segments from the bank 1.2.1 8
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