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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fragoulis, D. Rousopoulos, G. Panagopoulos, T. Alexiou, C. Papaodysseus, C. |
| Copyright Year | 1991 |
| 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. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 898 |
| Ending Page | 908 |
| Page Count | 11 |
| File Size | 204914 |
| File Format | |
| ISSN | 1053587X |
| Volume Number | 49 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-04-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pattern recognition Frequency System testing Multiple signal classification Speech Character recognition Feature extraction Spatial databases Broadcasting Performance evaluation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering |
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