Title :
A simplified attributed graph grammar for high-level music recognition
Author :
Baumann, Stephan
Author_Institution :
German Res. Center for Artificial Intelligence, Kaiserslautern, Germany
Abstract :
This paper describes a simplified attributed programmed graph grammar to represent and process a-priori knowledge about common music notation. The presented approach serves as a high-level recognition stage and is interlocked to previous low-level recognition phases in our entire optical music recognition system (DOREMIDI++). The implemented grammar rules and control diagrams describe a declarative knowledge base to drive a transformation algorithm. This transformation converts the results of symbol recognition stages to a symbolic representation of the musical score
Keywords :
attribute grammars; character recognition; document image processing; graph grammars; music; attributed graph grammar; declarative knowledge base; graph grammar; music recognition; symbolic representation; Acoustic applications; Artificial intelligence; Circuit testing; Handwriting recognition; Multiple signal classification; Music; Ordinary magnetoresistance; Shape; System testing; Writing;
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
DOI :
10.1109/ICDAR.1995.602096
