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Conjoined Audio Fingerprint based on Interhash and Intra hash Algorithms

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초록

In practice, the most important performance parameters for music information retrieval (MIR) service are robustness of fingerprint in real noise environments and recognition accuracy when the obtained query clips are matched with the an entry in the database. To satisfy these conditions, we proposed a conjoined fingerprint algorithm for use in massive MIR service. The conjoined fingerprint scheme uses interhash and intrahash algorithms to produce a robust fingerprint scheme in real noise environments. Because the interhash and intrahash algorithms are masked in the predominant pitch estimation, a compact fingerprint can be produced through their relationship. Experimental performance comparison results showed that our algorithms were superior to existing algorithms, i.e., the sub-mask and Philips algorithms, in real noise environments.

Abstract

In practice, the most important performance parameters for music information retrieval (MIR) service are robustness of fingerprint in real noise environments and recognition accuracy when the obtained query clips are matched with the an entry in the database. To satisfy these conditions, we proposed a conjoined fingerprint algorithm for use in massive MIR service. The conjoined fingerprint scheme uses interhash and intrahash algorithms to produce a robust fingerprint scheme in real noise environments. Because the interhash and intrahash algorithms are masked in the predominant pitch estimation, a compact fingerprint can be produced through their relationship. Experimental performance comparison results showed that our algorithms were superior to existing algorithms, i.e., the sub-mask and Philips algorithms, in real noise environments.

참고문헌 (8)

  1. P. Cano, "A Review of Audio Fingerprinting", J. VLSI Signal Processing Systems for Signal Image Video Technology, 41(3), pp.271~284 (2005)
  2. J. Haitsma, "A Highly Robust Audio Fingerprinting System", Proc. Of the 3rd Int. Symposium on Music Information Retrieval, pp.144~148 (2002)
  3. Mansoo Park, "Frequency-Temporal Filtering for a Robust Audio Fingerprinting Scheme in Real-Noise Environments", ETRI Journal, 28(4), pp.509~512 (2006), 한국전자통신연구원
  4. Wooram Son, "Sub-fingerprint Masking for a Robust Audio Fingerprinting System in Real-noise Environment for Portable Consumer Devices", IEEE Transactions on Consumer Electronics, 56(1), pp.156~160 (2010)
  5. J. Song, "Mid-level music melody representation of polyphonic audio for query-by-humming system", International Symposium on Music Information Retrieval (2002)
  6. J. Song, "Query by humming: matching humming query to polyphonic audio", IEEE International Conference on Multimedia and Expo (2002)
  7. J. Chen, "Cepstrum derived from Differentiated Power Spectrum for Robust Speech Recognition", Speech Communication, 41, pp.469~484 (2003)
  8. Ho-Young Jung, "Filtering of Filter-Bank Energies for Robust Speech Recognition", ETRI Journal, 26(3), pp.273~276 (2004), 한국전자통신연구원

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