Audio Fingerprinting: Nearest Neighbor Search in High Dimensional Binary Spaces
Journal of VLSI Signal Processing Systems
Speech Hashing Algorithm Based on Short-Time Stability
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
A unified approach to content-based and fault tolerant music identification
WEDELMUSIC'02 Proceedings of the Second international conference on Web delivering of music
Underwater target recognition with sonar fingerprint
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Digital Signal Processing
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A new methodology is presented for the automated recognition-identification of musical recordings that have suffered from a high degree of playing speed and frequency band distortion. The procedure of recognition is essentially based on the comparison between an unknown musical recording and a set of model ones, according to some predefined specific characteristics of the signals. In order to extract these characteristics from a musical recording, novel feature extraction algorithms are employed. This procedure is applied to the whole set of model musical recordings, thus creating a model characteristic database. Each time we want an unknown musical recording to be identified, the same procedure is applied to it, and subsequently, the derived characteristics are compared with the database contents via an introduced set of criteria. The proposed methodology led to the development of a system whose performance was extensively tested with various types of broadcasted musical recordings. The system performed successful recognition for the 94% of the tested recordings. It should be noted that the presented system is parallelizable and can operate in real time