Computing Structural Descriptions of Music through the Identification of Representative Excerpts from Audio Files

Ong BS. Computing Structural Descriptions of Music through the Identification of Representative Excerpts from Audio Files. In: AES Conference: 25th International Conference: Metadata for Audio. Audio Engineering Society; 2004. Paper 4-3. Available from: https://aes.org/publications/elibrary-page/?id=12812

@inproceedings{Ong2004_12812,
  author = {Ong, Bee-Suan},
  title = {{Computing Structural Descriptions of Music through the Identification of Representative Excerpts from Audio Files}},
  booktitle = {AES Conference: 25th International Conference: Metadata for Audio},
  note = {Paper 4-3},
  year = {2004},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=12812}
}

TY  - CPAPER
TI  - Computing Structural Descriptions of Music through the Identification of Representative Excerpts from Audio Files
AU  - Ong, Bee-Suan
T2  - AES Conference: 25th International Conference: Metadata for Audio
M1  - Paper 4-3
PY  - 2004
DA  - 2004/06/06
UR  - https://aes.org/publications/elibrary-page/?id=12812
PB  - Audio Engineering Society
LA  - en
AB  - With the rapid growth of audio databases, many music retrieval applications have employed metadata descriptions to facilitate better handling of huge databases. Music structure creates the uniqueness identity for each music piece. Therefore, structural description is capable of providing a powerful way of interacting with audio content, and serves as a linkage between low-level description and higher-level descriptions of audio (e.g. audio summarization, audio fingerprinting, etc.). Identification of representative musical excerpts is the primary step towards the goal of generating structural descriptions of audio signals. In this paper, we will provide a systematic review of the existing work on extracting musical structure descriptors from music files and will present, discuss, and evaluate various approaches in identifying representative musical excerpts of music audio signals.
ER  -