Recognition and Prediction of Music - A Machine Learning Approach

Szczerba M. Recognition and Prediction of Music - A Machine Learning Approach. In: AES Convention 106. Audio Engineering Society; 1999. Paper 4904. Available from: https://aes.org/publications/elibrary-page/?id=8276

@inproceedings{Szczerba1999_8276,
  author = {Szczerba, Marek},
  title = {{Recognition and Prediction of Music - A Machine Learning Approach}},
  booktitle = {AES Convention 106},
  note = {Paper 4904},
  year = {1999},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=8276}
}

TY  - CPAPER
TI  - Recognition and Prediction of Music - A Machine Learning Approach
AU  - Szczerba, Marek
T2  - AES Convention 106
M1  - Paper 4904
PY  - 1999
DA  - 1999/05/06
UR  - https://aes.org/publications/elibrary-page/?id=8276
PB  - Audio Engineering Society
LA  - en
AB  - This paper contains a description of a machine-learning-based system for recognition and prediction of music. The presented system uses advanced data-mining algorithms: neural networks and rough-sets. The system was applied for two main purposes: recognition of musical: structures (phrase, rhythm and harmony) and for the prediction of musical elements (melody, rhythm and harmony). The system was optimized for each of the purposes. The problems related to the optimization process are presented. Conclusions concerning application of the machine learning methods to the music domain are derived and included.
ER  -