On the automated recognition of seriously distorted musical recordings

Fragoulis, D; Rousopoulos, G; Panagopoulos, T; Alexiou, C; Papaodysseus, C

dc.contributor.author	Fragoulis, D	en
dc.contributor.author	Rousopoulos, G	en
dc.contributor.author	Panagopoulos, T	en
dc.contributor.author	Alexiou, C	en
dc.contributor.author	Papaodysseus, C	en
dc.date.accessioned	2014-03-01T01:16:50Z
dc.date.available	2014-03-01T01:16:50Z
dc.date.issued	2001	en
dc.identifier.issn	1053-587X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14251
dc.subject	Automatic music recognition	en
dc.subject	Distorted in frequency recordings	en
dc.subject	Fuzzy logic and music	en
dc.subject	Music pattern recognition	en
dc.subject	Music processing	en
dc.subject	Musical recording automated recognition	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Acoustic signal processing	en
dc.subject.other	Algorithms	en
dc.subject.other	Database systems	en
dc.subject.other	Feature extraction	en
dc.subject.other	Frequencies	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Parallel processing systems	en
dc.subject.other	Pattern recognition	en
dc.subject.other	Performance	en
dc.subject.other	Sound recording	en
dc.subject.other	Automated recognition-identification	en
dc.subject.other	Automatic music recognition	en
dc.subject.other	Frequency band distortion	en
dc.subject.other	Frequency recording	en
dc.subject.other	Music pattern recognition	en
dc.subject.other	Musical recording	en
dc.subject.other	Acoustic distortion	en
dc.title	On the automated recognition of seriously distorted musical recordings	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/78.912932	en
heal.identifier.secondary	http://dx.doi.org/10.1109/78.912932	en
heal.language	English	en
heal.publicationDate	2001	en
heal.abstract	In this paper, 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.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Signal Processing	en
dc.identifier.doi	10.1109/78.912932	en
dc.identifier.isi	ISI:000167587600021	en
dc.identifier.volume	49	en
dc.identifier.issue	4	en
dc.identifier.spage	898	en
dc.identifier.epage	908	en