Musical instrument recognition using ICA-based transform of features and discriminatively trained HMMs

@article{Eronen2003MusicalIR,
  title={Musical instrument recognition using ICA-based transform of features and discriminatively trained HMMs},
  author={A. Eronen},
  journal={Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.},
  year={2003},
  volume={2},
  pages={133-136 vol.2}
}
  • A. Eronen
  • Published 2003
  • Computer Science
  • Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.
In this paper, we describe a system for the recognition of musical instruments from isolated notes or drum samples. We first describe a baseline system that uses mel-frequency cepstral coefficients and their first derivatives as features, and continuous-density hidden Markov models (HMMs). Two improvements are proposed to increase the performance of this baseline system. First, transforming the features to a base with maximal statistical independence using independent component analysis can… Expand
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