Title :
On the automated recognition of seriously distorted musical recordings
Author :
Fragoulis, Dimitrios ; Rousopoulos, George ; Panagopoulos, Thanasis ; Alexiou, Constantin ; Papaodysseus, Constantin
Author_Institution :
Div. of Comput. Sci., Nat. Tech. Univ. of Athens, Greece
fDate :
4/1/2001 12:00:00 AM
Abstract :
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
Keywords :
audio coding; audio recording; feature extraction; music; pattern matching; pattern recognition; CD; audio coding; automated musical recording recognition; automated recognition-identification; compact disc; distorted musical recordings; feature extraction algorithms; frequency band distortion; model characteristic database; music pattern recognition; parallelizable system; pattern matching; playing speed distortion; real time operation; signal characteristics; tested recordings; Broadcasting; Character recognition; Feature extraction; Frequency; Multiple signal classification; Pattern recognition; Performance evaluation; Spatial databases; Speech; System testing;
Journal_Title :
Signal Processing, IEEE Transactions on