Skip to main content
Springer Nature Link
Log in

Robust audio fingerprinting using peak-pair-based hash of non-repeating foreground audio in a real environment

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

In this paper, we propose a high-performance audio fingerprinting system used in real-world query-by-example applications for acoustic audio-based content identification, especially for use in heterogeneous portable consumer devices or on-line audio distributed system. In the proposed method, audio fingerprints are generated using a modulated complex lapped transform-based non-repeating foreground audio extraction and an adaptive thresholding method for prominent peak detection. Effective matching is performed using a robust peak-pair-based hash function of non-repeating foreground audio to protect against noise, echo, artifacts from pitch-shifting, time-stretching, resampling, equalization, or compression. Experimental results confirm that the proposed method is quite robust in various distorted conditions and achieves preliminarily promising accuracy results.

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
$34.99 /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 excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Cano, P., Batlle, E., Kalker, T., Haitsma, J.: A review of algorithms for audio fingerprinting. In: International Workshop on Multimedia Signal Processing, pp. 169–173 (2002)

  2. Li, W., Xiao, C., Liu, Y.: Low-order auditory Zernike moment: a novel approach for robust music identification in the compressed domain. EURASIP J. Adv. Sig. Process. 1, 1–15 (2013)

    Google Scholar 

  3. Sinitsyn, A.: Duplicate song detection using audio fingerprinting for consumer electronics devices. In: IEEE International Symposium on Consumer Electronics (ISCE06), St. Petersburg, Russia, pp. 1–6 (2006)

  4. Cerquides, J.: A real time audio fingerprinting system for advertisement tracking and reporting in FM radio. In: 17th International Conference on Radioelektronika, Brno, Czech, pp. 1–4 (2007)

  5. Haitsma, J., Kalker, T.: A highly robust audio fingerprinting system. In: 3rd International Society for Music Information Retrieval Conference (ISMIR), Paris, France, pp. 107–115 (2002)

  6. Liu, Y., Yun, H.-S., Kim, N.S.: Audio fingerprinting based on multiple hashing in DCT domain. IEEE Sig. Process. Lett. 6(6), 525–528 (2009)

    Article  Google Scholar 

  7. Chandrasekhar, V., Sharifi, M., Ross, D.A.: Survey and evaluation of audio fingerprinting schemes for mobile query-by-example applications. In: 12th International Society for Music Information Retrieval Conference (ISMIR), Miami, USA, pp. 801–806 (2011)

  8. Pan, X., Yu, X., Deng, J., Yang, W., Wang, H.: Audio fingerprinting based on local energy centroid. In: IET International Communication Conference on Wireless Mobile and Computing (CCWMC), Shanghai, China, pp. 351–354 (2011)

  9. Baluja, S., Covel, M.: Audio fingerprinting: combining computer vision and data-stream processing. In: International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Honolulu, Hawaii, pp. 2:213–2:216 (2007)

  10. Anguera, X., Garzon, A., Adamek, T.: MASK: robust local feature for audio fingerprinting. In: International Conference on Multimedia and Expo (ICME), pp. 455–460 (2012)

  11. Wang, A.: An industrial strength audio search algorithm. In: 4th International Society for Music Information Retrieval Conference (ISMIR), Baltimore, pp. 7–13 (2003)

  12. Kim, H.-G., Kim, J.Y.: Robust audio fingerprinting method using prominent peak pair based on modulated complex lapped transform. ETRI J. 36(6), 999–1007 (2014)

    Article  Google Scholar 

  13. Fenet, S., Richard, G., Grenier, Y.: A scalable audio fingerprint method with robustness to pitch-shifting. In: 12th International Society for Music Information Retrieval Conference, Taipei, Taiwan, pp. 121–126 (2011)

  14. Malvar, H.: Fast algorithm for the modulated complex lapped transform. IEEE Sig. Process. Lett. 10(1), 8–10 (2003)

    Article  Google Scholar 

  15. Rafii, Z., Pardo, B.: Repeating pattern extraction technique (REPET): a simple method for music/voice separation. EEE Trans. Audio Speech Lang. Process. 21(1), 73–84 (2013)

    Article  Google Scholar 

  16. Liutkus, A., Rafii, Z., Badeau, R., Pardo, B., Richard, G.: Adaptive filtering for music/voice separation exploiting the repeating musical structure. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, pp. 53–56 (2012)

Download references

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2013R1A1A2007601). And this research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1016) supervised by the IITP (Institute for Information & communications Technology Promotion), and Kwangwoon Research Grant 2014.

Author information

Authors and Affiliations

  1. Department of Electronics Convergence Engineering, Kwangwoon University, 20 Gwangun-ro, Nowon-gu, Seoul, Korea

    Hyoung-Gook Kim

  2. Department of Radio Sciences and Engineering, Kwangwoon University, 20 Gwangun-ro, Nowon-gu, Seoul, Korea

    Hye-Seung Cho

  3. Department of Electronics and Computer Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju, Korea

    Jin Young Kim

Authors
  1. Hyoung-Gook Kim
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Hye-Seung Cho
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Jin Young Kim
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Hyoung-Gook Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, HG., Cho, HS. & Kim, J.Y. Robust audio fingerprinting using peak-pair-based hash of non-repeating foreground audio in a real environment. Cluster Comput 19, 315–323 (2016). https://doi.org/10.1007/s10586-015-0523-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-015-0523-z

Keywords