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An audio fingerprinting extraction algorithm based on lifting wavelet packet and improved optimal-basis selection

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Abstract

Audio fingerprinting technology is widely applied to the analysis and processing of digital signal, especially in the application of speech recognition which is one of the most popular fields of the intelligent multimedia and artificial intelligence. Traditional audio fingerprinting extraction algorithm is based on the decomposition and reconstruction of the wavelet packet. But the requirement of computational capacity and memory is so large. So this paper proposed an algorithm which is based on the lifting wavelet packet and the improved optimal-basis selection to find the coefficient of optimal wavelet packet. Then the average of the logarithmic energy entropy is adopted as the characteristic parameter. And the capacity of computing and memory is better than the traditional algorithm because of the lifting wavelet packet which is more suitable for processing of speech online and the design of intelligent multimedia. And the experiment results indicate that this algorithm is not only robust for the audio which is handled by some kinds of methods and can reflect the overall characteristics of the audio very well, but also has good distinguishability between different audio.

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Acknowledgments

The authors would like to appreciate all anonymous reviewers for their insightful comments and constructive suggestions to polish this paper in high quality. This research was supported by the ShanghaiScience and Technology Innovation Action Plan Project (16111107502, 17511107203), the National Natural Science Foundation of China (61502220), the Zhejiang Provincial Natural Science Foundation of China(No.LY14F020044), the program for tackling key problems in Henan science and technology (No.172102310636) and the Nanjing Leading Science and Technology Entrepreneurial Talents Introduction Program Funded Project (2014A090002).

Funding

This study was supported by the Shanghai Science and Technology Innovation Action Plan Project (16111107502, 17511107203),the National Natural Science Foundation of China (61502220), the Zhejiang Provincial Natural Science Foundation of China (No.LY14F020044), the program for tackling key problems in Henan science and technology (No.172102310636) and the Nanjing Leading Science and Technology Entrepreneurial Talents Introduction ProgramFunded Project (2014A090002).

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Authors and Affiliations

  1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

    Yuantao Jiang & Chunxue Wu

  2. School of Art and Design, Shanghai University of Engineering Science, Shanghai, China

    Kaifa Deng

  3. School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, USA

    Yan Wu

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  1. Yuantao Jiang
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  2. Chunxue Wu
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  3. Kaifa Deng
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  4. Yan Wu
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Correspondence to Chunxue Wu.

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Jiang, Y., Wu, C., Deng, K. et al. An audio fingerprinting extraction algorithm based on lifting wavelet packet and improved optimal-basis selection. Multimed Tools Appl 78, 30011–30025 (2019). https://doi.org/10.1007/s11042-018-6802-y

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