A simple network has been built which is trained to differentiate between different classifications of timbre. The net is given a training set of several thousand spectra with particular characteristics, and it rapidly learns to differentiate between timbre-classes based on these characteristics. Although the network model is rather crude, the system actually can learn to identify timbral features. Timbre remains one of the most poorly-understood areas of music theory and music cognition. The CMC has successfully completed a number of archive projects, earning a well-deserved reputation as one of the few places available with both the correct equipment and trained expertise to do critical archival work.
All software is in the public domain, and source code is distributed with the files.
All files are in gzipped tarred format, and compile under Irix.