Descriptors are encoded with an alphanumeric ID, which acts as a form of shorthand and notational hierarchy for the lexicon. Attributes that address quantifiable features of time, frequency and timbre are measured with Semantic Differential (SD) scales. Up to 81 descriptors can be selected simultaneously across any or all of the trees. Attributes are populated with over 2500 descriptors, organised categorically in a hierarchical tree-branch structure, and distributed across three interrelated trees called Source, Sound and Subject. At the heart of the lexicon lie 35 Attributes of percussion instrument morphology, excitation, spectral/temporal features, descriptive adjectives and onomatopoeia. In the applied environment it can be used to tag percussion samples in sound libraries with a comprehensive set of semantic descriptors.
As a theoretical tool it can be used to learn about percussion, compare similarities and differences between sounds, and explore correlations between sound and source. An ontology of sorts, PAL offers an approach to describing the ‘state’ of virtually any percussion instrument producing a specific sound at a moment in time, from multiple perspectives simultaneously. However, none exist that exclusively address drums and percussion in the form that is proposed with PAL.
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Taxonomies, ontologies and folksonomies of semantic descriptors for musical instruments, music recordings, music samples and sound effects exist in various domains including the Semantic Web, online databases and stand-alone software applications. The challenge of providing semantically rich information about recorded sounds – and the sources that produce them – has inspired a number of approaches and schemes seeking to address the issue. Developing a means of effectively describing the diversity of percussion is the primary goal of this research, and thus the Percussive Audio Lexicon (PAL) is proposed. Compared with other musical instruments, percussion is unparalleled in its diversity, and the palette of sonic and timbral possibilities is vast.
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