• DocumentCode
    238018
  • Title

    Efficient selection of rhythmic features for musical instrument recognition

  • Author

    Singh, Chetan Pratap ; Kumar, T. Kishore

  • Author_Institution
    Dept. of E.C.E., Nat. Inst. of Technol., Warangal, India
  • fYear
    2014
  • fDate
    8-10 May 2014
  • Firstpage
    1393
  • Lastpage
    1397
  • Abstract
    Various feature schemes have been proposed through acoustic study and pattern recognition research. In this paper our main intention is to investigate the performance of different rhythmic feature schemes as well as find a good rhythmic feature combination for a robust musical instrument classifier. Lots of work has been done on speech and speaker recognition. Musical instrument recognition is an important aspect of music information retrieval system. In this paper we have discussed different rhythmic features namely beat histogram, dynamic range, spectral crest facture, mean, variance. kurtosis etc.[1].
  • Keywords
    information retrieval; musical instruments; pattern classification; signal classification; acoustic study; beat histogram; dynamic range; music information retrieval system; musical instrument recognition; pattern recognition research; rhythmic feature combination; rhythmic feature schemes; robust musical instrument classifier; speaker recognition; spectral crest facture; speech recognition; Conferences; Dynamic range; Feature extraction; Histograms; Instruments; Multiple signal classification; Timbre; Timbre features; histogram; rhythmic features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
  • Conference_Location
    Ramanathapuram
  • Print_ISBN
    978-1-4799-3913-8
  • Type

    conf

  • DOI
    10.1109/ICACCCT.2014.7019329
  • Filename
    7019329