Tonic and scale recognition in Persian audio musical signals
- Resource Type
- Conference
- Authors
- Heydarian, Peyman; Jones, Lewis
- Source
- 2014 12th International Conference on Signal Processing (ICSP) Signal Processing (ICSP), 2014 12th International Conference on. :18-21 Oct, 2014
- Subject
- Signal Processing and Analysis
Histograms
Training
Music information retrieval
Multiple signal classification
Transforms
Tuning
Educational institutions
Persian scale identification
tonic detection
maqàm
mode
dastgàh
santur
chroma
Pitch Class Profiles
Bit-masking
Manhattan distance
Machine Learning
DSP
Computational musicology
- Language
- ISSN
- 2164-5221
2164-523X
This paper proposes methods for computational identification of the tonic and scale in Persian audio musical signals. The chroma, a simplified spectrum is taken as the feature set and Bit-masking and Manhattan distance are used as the classifiers. The results are applicable to various musical traditions in the Mediterranean and the Near East. This approach enables content-based analysis of, and content-based searches of, musical archives.