[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Efficient music note recognition based on a self-organizing map tree and linear vector quantization

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Using classical signal processing and filtering techniques for music note recognition faces various kinds of difficulties. This paper proposes a new scheme based on neural networks for music note recognition. The proposed scheme uses three types of neural networks: time delay neural networks, self-organizing maps, and linear vector quantization. Experimental results demonstrate that the proposed scheme achieves 100% recognition rate in moderate noise environments. The basic design of two potential applications of the proposed scheme is briefly demonstrated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Cemgil A, Kappen H, Barber D (2006) A generative model for music transcription. Audio Speech Lang Process 14(2):679–694

    Article  Google Scholar 

  • Klapuri A, Eronen A, Astola J (2006) Analysis of the meter of acoustic musical signals. Audio Speech Lang Process 14(1):342–355

    Article  Google Scholar 

  • Kohonen T (2001) Self-organizing maps. Springer, Heidelberg

  • Marolt M (2004) A connectionist approach to automatic transcription of polyphonic piano music. Multimedia 6(3):439–449

    Article  Google Scholar 

  • Park K, Yoon W, Lee K et al (2005) MRTB framework: a robust content-based music retrieval and browsing. Consum Electron 51(1):117–122

    Article  Google Scholar 

  • Pikrakis A, Theodoridis S, Kamarotos D (2006) Classification of musical patterns using variable duration hidden Markov models. Audio Speech Lang Process 14(5):1795–1807

    Article  Google Scholar 

  • Rowe R (2001) Machine musicianship. The MIT Press, Cambridge

  • Schmidt A, Stone T (2002) Music classification and identification system. Technical report, University of Colorado

  • Shen J, Shepherd J, Ngu A (2006) Towards effective content-based music retrieval with multiple acoustic feature combination. Multimedia 8(6):1179–1189

    Article  Google Scholar 

  • Thornburg H, Leistikow R, Berger J (2007) Melody extraction and musical onset detection via probabilistic models of framewise STFT peak data. Audio Speech Lang Process 15(4):1257–1272

    Article  Google Scholar 

  • Wan E (1990) Temporal back-propagation for FIR neural networks. In: Proceedings of neural networks IJCNN’90, Washington, pp 575–580

  • Ying S, Yu G, Kuo S (2005) A robust hybrid feedback active noise cancellation headset. Speech Audio Process 13(4):607–617

    Article  Google Scholar 

  • Yu S, Hu J (2001) Controller design for active noise cancellation headphones usingexperimental raw data. Mechatronics 6(4):483–490

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Northern Illinois University, Dekalb, IL, USA

    Khalid Youssef & Peng-Yung Woo

Authors
  1. Khalid Youssef
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peng-Yung Woo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Khalid Youssef.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Youssef, K., Woo, PY. Efficient music note recognition based on a self-organizing map tree and linear vector quantization. Soft Comput 13, 1187–1198 (2009). https://doi.org/10.1007/s00500-009-0416-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-009-0416-2

Keywords

Search

Navigation