DCT based multiple hashing technique for robust audio fingerprinting

Authors:
Yu Liu; Kiho Cho; Hwan Sik Yun; Jong Won Shin; Nam Soo Kim
Affiliations:
School of Electrical Engineering and INMC, Seoul National University, 151-742, Korea;School of Electrical Engineering and INMC, Seoul National University, 151-742, Korea;School of Electrical Engineering and INMC, Seoul National University, 151-742, Korea;School of Electrical Engineering and INMC, Seoul National University, 151-742, Korea;School of Electrical Engineering and INMC, Seoul National University, 151-742, Korea
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Coherent bag-of audio words model for efficient large-scale video copy detection

Proceedings of the ACM International Conference on Image and Video Retrieval

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Abstract

Audio fingerprinting techniques should successfully perform content-based audio identification even when the audio files are slightly or seriously distorted. In this paper, we present a novel audio fingerprinting technique based on combining fingerprint matching results for multiple hash tables in order to improve the robustness of hashing. Multiple hash tables are built based on the discrete cosine transform (DCT) which is applied to the time sequence of energies in each sub-band. Experimental results show that the recognition errors are significantly reduced compared with Philips Robust Hash (PRH) [1] under various distortions.