A Mixture-of-Experts Approach for Note Onset Detection

Degara N, Pena A, Sobreira-Seoane M, Torres-Guijarro S. A Mixture-of-Experts Approach for Note Onset Detection. In: AES Convention 126. Audio Engineering Society; 2009. Paper 7757. Available from: https://aes.org/publications/elibrary-page/?id=14953

@inproceedings{Degara2009_14953,
  author = {Degara, Norberto and Pena, Antonio and Sobreira-Seoane, Manuel and Torres-Guijarro, Soledad},
  title = {{A Mixture-of-Experts Approach for Note Onset Detection}},
  booktitle = {AES Convention 126},
  note = {Paper 7757},
  year = {2009},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=14953}
}

TY  - CPAPER
TI  - A Mixture-of-Experts Approach for Note Onset Detection
AU  - Degara, Norberto
AU  - Pena, Antonio
AU  - Sobreira-Seoane, Manuel
AU  - Torres-Guijarro, Soledad
T2  - AES Convention 126
M1  - Paper 7757
PY  - 2009
DA  - 2009/05/06
UR  - https://aes.org/publications/elibrary-page/?id=14953
PB  - Audio Engineering Society
LA  - en
AB  - Finding the starting time of events (onsets) is useful in a number of applications for audio signals. The goal of this paper is to present a combination of techniques for automatic detection of events in audio signals. The proposed system uses a supervised classification algorithm to combine a set of features extracted from the audio signal and reduce the original signal to a robust detection function. Onsets are obtained by using a simple peak-picking algorithm. This paper describes the analysis system used to extract the features and the details of the neural network algorithm used to combine them. We conclude by comparing the performance of the proposed algorithm with the system that obtained the first place in the 2005 Music Information Retrieval Evaluation eXchange.
ER  -