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A spectrogram-based audio fingerprinting system for content-based copy detection

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Abstract

This paper presents a novel audio fingerprinting method that is highly robust to a variety of audio distortions. It is based on an unconventional audio fingerprint generation scheme. The robustness is achieved by generating different versions of the spectrogram matrix of the audio signal by using a threshold based on the average of the spectral values to prune this matrix. We transform each version of this pruned spectrogram matrix into a 2-D binary image. Multiple versions of these 2-D images suppress noise to a varying degree. This varying degree of noise suppression improves likelihood of one of the images matching a reference image. To speed up matching, we convert each image into an n-dimensional vector, and perform a nearest neighbor search based on this n-dimensional vector. We give results with two different feature parameters and their combination. We test this method on TRECVID 2010 content-based copy detection evaluation dataset, and we validate the performance on TRECVID 2009 dataset also. Experimental results show the effectiveness of these features even when the audio is distorted. We compare the proposed method to two state-of-the-art audio copy detection systems, namely NN-based and Shazam systems. Our method by far outperforms Shazam system for all audio transformations (or distortions) in terms of detection performance, number of missed queries and localization accuracy. Compared to NN-based system, our approach reduces minimal Normalized Detection Cost Rate (min NDCR) by 23 % and improves localization accuracy by 24 %.

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Notes

  1. These are only approximations of the speed difference between the query and the corresponding reference. For example, −180 % means that the query is approximately 2.8 times slower than the reference (1 s of the query corresponds to approximately 0.36 s of the reference).

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Authors and Affiliations

  1. ÉTS (École de Technologie Supérieure), Montreal, Canada

    Chahid Ouali & Pierre Dumouchel

  2. CRIM (Computer Research Institute of Montreal), Montreal, Canada

    Chahid Ouali & Vishwa Gupta

Authors
  1. Chahid Ouali
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  2. Pierre Dumouchel
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  3. Vishwa Gupta
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Correspondence to Chahid Ouali.

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Ouali, C., Dumouchel, P. & Gupta, V. A spectrogram-based audio fingerprinting system for content-based copy detection. Multimed Tools Appl 75, 9145–9165 (2016). https://doi.org/10.1007/s11042-015-3081-8

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  • DOI: https://doi.org/10.1007/s11042-015-3081-8

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