Tonic and scale recognition in Persian audio musical signals

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.