Music genre classification using novel features and a weighted voting method

@article{Jang2008MusicGC,
  title={Music genre classification using novel features and a weighted voting method},
  author={Dalwon Jang and Minho Jin and C. Yoo},
  journal={2008 IEEE International Conference on Multimedia and Expo},
  year={2008},
  pages={1377-1380}
}
  • Dalwon Jang, Minho Jin, C. Yoo
  • Published 2008
  • Computer Science
  • 2008 IEEE International Conference on Multimedia and Expo
  • This paper proposes a novel music genre classification system based on two novel features and a weighted voting. The proposed features, modulation spectral flatness measure (MSFM) and modulation spectral crest measure (MSCM), represent the time-varying behavior of a music and indicate the beat strength. The weighted voting method determines the music genre by summarizing the classification results of consecutive time segments. Experimental results show that the proposed features give more… CONTINUE READING

    Figures and Topics from this paper.

    Music genre classification based on local feature selection using a self-adaptive harmony search algorithm
    • 32
    • Highly Influenced
    Content-based music genre classification using timbral feature vectors and support vector machine
    • 10
    • Highly Influenced
    A Survey of Evaluation in Music Genre Recognition
    • 91
    • Open Access
    Music Genre Classification Using Spectral Analysis and Sparse Representation of the Signals
    • 11
    • Open Access

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 13 REFERENCES
    A comparative study on content-based music genre classification
    • 414
    • Open Access
    Music type classification by spectral contrast feature
    • 218
    • Highly Influential
    • Open Access
    Musical genre classification of audio signals
    • 2,384
    • Highly Influential
    • Open Access
    Automatic Music Genre Classification using Modulation Spectral Contrast Feature
    • 33
    • Highly Influential
    • Open Access
    Features and classifiers for the automatic classification of musical audio signals
    • 118
    • Open Access
    Probability Estimates for Multi-class Classification by Pairwise Coupling
    • 1,783
    • Open Access
    Modulation-scale analysis for content identification
    • 79
    • Open Access
    MARSYAS SUBMISSIONS TO MIREX 2007
    • 62
    • Highly Influential
    • Open Access
    Spoken Language Processing
    • 919
    A large set of audio features for sound description (similarity and classification) in the CUIDADO p
    • 601