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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Robust Speech Hash Function

  • Chen, Ning (School of Communication and Information Engineering, Shanghai University) ;
  • Wan, Wanggen (School of Communication and Information Engineering, Shanghai University)
  • Received : 2009.07.27
  • Accepted : 2009.12.18
  • Published : 2010.04.30
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Abstract

In this letter, we present a new speech hash function based on the non-negative matrix factorization (NMF) of linear prediction coefficients (LPCs). First, linear prediction analysis is applied to the speech to obtain its LPCs, which represent the frequency shaping attributes of the vocal tract. Then, the NMF is performed on the LPCs to capture the speech's local feature, which is then used for hash vector generation. Experimental results demonstrate the effectiveness of the proposed hash function in terms of discrimination and robustness against various types of content preserving signal processing manipulations.

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References

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