Recently,many audio search sites headed by Google have used audio fingerprinting technology to search for the same audio and protect the music copyright using one part of the audio data.However,if there are fingerprin...Recently,many audio search sites headed by Google have used audio fingerprinting technology to search for the same audio and protect the music copyright using one part of the audio data.However,if there are fingerprints per audio file,then the amount of query data for the audio search increases.In this paper,we propose a novel method that can reduce the number of fingerprints while providing a level of performance similar to that of existing methods.The proposed method uses the difference of Gaussians which is often used in feature extraction during image signal processing.In the experiment,we use the proposed method and dynamic time warping and undertake an experimental search for the same audio with a success rate of 90%.The proposed method,therefore,can be used for an effective audio search.展开更多
Audio copyright is a crucial issue in the music industry,as it protects the rights and interests of creators and distributors.This paper studies the current situation of digital music copyright certification and propo...Audio copyright is a crucial issue in the music industry,as it protects the rights and interests of creators and distributors.This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on“blockchain+edge computing mode,”abbreviated as MBE,by integrating edge computing into the Hyperledger Fabric system.MBE framework compresses and splits the audio into small chunks,performs Fast Fourier Transform(FFT)to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information.After being confirmed by various nodes on the Fabric alliance chain,audio fingerprint information and copyright owner information are recorded on the chain and broadcast to all participants.Blockchain technology’s characteristics of being tamper-proof and traceable not only reform the trust mechanism of copyright protection but also endow edge computing with the ability to resist tampering and single-point attack,greatly enhancing the robustness of the music copyright certification system.Meanwhile,edge computing mode improves Fabric blockchain’s processing speed and transaction throughput.Experimental results show that MBE’s performance is better than traditional systems regarding efficiency,storage demand and security.Compared to the traditional Fabric system without edge computing mode,MBE exhibits a 53%higher deposition efficiency and a 48%lower storage space requirement.展开更多
文摘Recently,many audio search sites headed by Google have used audio fingerprinting technology to search for the same audio and protect the music copyright using one part of the audio data.However,if there are fingerprints per audio file,then the amount of query data for the audio search increases.In this paper,we propose a novel method that can reduce the number of fingerprints while providing a level of performance similar to that of existing methods.The proposed method uses the difference of Gaussians which is often used in feature extraction during image signal processing.In the experiment,we use the proposed method and dynamic time warping and undertake an experimental search for the same audio with a success rate of 90%.The proposed method,therefore,can be used for an effective audio search.
基金supported by Jiangxi Provincial Natural Science Foundation under Grant Nos.20224BAB212015,20224ACB202007Jiangxi Province Science and Technology Project (03 Special 5G Project)under Grant No.20224ABC03A13+1 种基金the Foundation of Jiangxi Educational Committee underGrant No.GJJ210338the National Natural Science Foundation of China (NSFC),under Grant No.61962026.
文摘Audio copyright is a crucial issue in the music industry,as it protects the rights and interests of creators and distributors.This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on“blockchain+edge computing mode,”abbreviated as MBE,by integrating edge computing into the Hyperledger Fabric system.MBE framework compresses and splits the audio into small chunks,performs Fast Fourier Transform(FFT)to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information.After being confirmed by various nodes on the Fabric alliance chain,audio fingerprint information and copyright owner information are recorded on the chain and broadcast to all participants.Blockchain technology’s characteristics of being tamper-proof and traceable not only reform the trust mechanism of copyright protection but also endow edge computing with the ability to resist tampering and single-point attack,greatly enhancing the robustness of the music copyright certification system.Meanwhile,edge computing mode improves Fabric blockchain’s processing speed and transaction throughput.Experimental results show that MBE’s performance is better than traditional systems regarding efficiency,storage demand and security.Compared to the traditional Fabric system without edge computing mode,MBE exhibits a 53%higher deposition efficiency and a 48%lower storage space requirement.
