DocumentCode
3326737
Title
A simplified attributed graph grammar for high-level music recognition
Author
Baumann, Stephan
Author_Institution
German Res. Center for Artificial Intelligence, Kaiserslautern, Germany
Volume
2
fYear
1995
fDate
14-16 Aug 1995
Firstpage
1080
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location
Montreal, Que.
Print_ISBN
0-8186-7128-9
Type
conf
DOI
10.1109/ICDAR.1995.602096
Filename
602096
Link To Document