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initial encoding at peripheral levels to its source-based representation at more central levels. Not only
can thi:> improve our basic understanding of auditory processing but also can suggest ways in which
humans can optimize their performance in detecting and evaluating signals of interest within their
acoustic environment.
6.4.4 Absolute Pitch. Absolute Tempo. Absolute Loudness
Daniel Levitin
Broadly speaking, my research is concerned with the psychology of structure and perceptual organization.
How does the brain organize the world around us. create categories, and parse a dense perceptual field?
To answer these questions. I have been examining principles of visual and auditory perception (how the
brain groups basic elements into objects).
More specifically, my current research projects include work on:
• absolute pitch, including issues about learning, etiology, and categorical perception
• circular statistical models for psychological research
• vowel perception
• memory for musical events
• perception of simultaneity of events (intra-modally and cross-modally)
• music perception and Williams' syndrome patients
• tone deafness/tune deafness, dysmelodia. and amusia
• the search for visual perceptual primitives
For more information, please see http://wvw-ccrma.stanford.edu/~levitin/research.html.
6.5 Machine Recognition in Music
6.5.1 Optical Recognition of Printed Music: A New Approach
Walter Hewlett
Recent projects in optical recognition of printed music have tended to give top priority to the extraction
of pitch symbols (i.e.. noteheads). Noteheads give some information about duration (i.e.. they are filled
or unfilled), but definitive information also requires the accurate reading of stems, flags, and beams.
Symbols for articulation (staccato marks, dynamics, slurs, and so forth) are sometimes ignored if the
intended use of the scanned material is in sound applications.
In an effort to create a scanning front-end for the CCARH databases of classical music, which are stored
in an attribute-rich format (MuseData) to support notation, sound, and analysis, we have taken the
following approach: large objects are identified first. This clarifies contextual properties that may bear
on pitch (key signatures, clef changes, octave-transposition signs), duration (beams, stems, and flags).
and articulation (slurs, ornaments, et al.). The pitch content of the notehead is the last item to be
recognized and completes the representation.
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