Efficient Musical Instrument Recognition on Solo Performance Music using Basic Features

David B, Richard G. Efficient Musical Instrument Recognition on Solo Performance Music using Basic Features. In: AES Conference: 25th International Conference: Metadata for Audio. Audio Engineering Society; 2004. Paper 2-5. Available from: https://aes.org/publications/elibrary-page/?id=12807

@inproceedings{David2004_12807,
  author = {David, Bertrand and Richard, Gael},
  title = {{Efficient Musical Instrument Recognition on Solo Performance Music using Basic Features}},
  booktitle = {AES Conference: 25th International Conference: Metadata for Audio},
  note = {Paper 2-5},
  year = {2004},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=12807}
}

TY  - CPAPER
TI  - Efficient Musical Instrument Recognition on Solo Performance Music using Basic Features
AU  - David, Bertrand
AU  - Richard, Gael
T2  - AES Conference: 25th International Conference: Metadata for Audio
M1  - Paper 2-5
PY  - 2004
DA  - 2004/06/06
UR  - https://aes.org/publications/elibrary-page/?id=12807
PB  - Audio Engineering Society
LA  - en
AB  - Musical instrument recognition has gained growing concern for the promise it holds towards advances in musical content description. The present study pursues the goal of showing the efficiency of some basic features for such a recognition task in the realistic situation where solo musical phrases are played. A large and varied database of sounds assembled from different commercial recordings is used to ensure better training and testing conditions, in terms of statistical efficiency. It is found that when combining cepstral features with others describing the audio signal spectral shape, a high recognition accuracy can be achieved in association with Support Vector Machine classification (especially when using a Radial Basis Function kernel).
ER  -