Music Recognition Using Blockchain Technology and Deep Learning

Abstract

The purposes are to recognize and classify different music characteristics and strengthen the copyright protection system for original digital music in the big data era. Deep learning (DL) and blockchain technology are applied and researched herein. Based on CNN (Convolutional Neural Network), a music recognition method combined with hashing learning is proposed. The error generated when outputting the binary hash code is considered, and the semantic similarity of the hash code is ensured. Besides, the application of blockchain technology in the current intellectual property protection in original music is discussed. According to digital music property rights protection needs, the system is divided into modules, and its functions are designed. The system ensures its various functions by applying the application protocol designed in the Algor and network. In the experiments, the MagnaTagATune dataset is selected to verify the performance of the proposed CRNNH (Convolutional Recurrent Neural Network Hashing) algorithm. The algorithm shows the best music recognition performance under different bit numbers. When the number of connections is about 100, the QPS value of the blockchain-based music property rights protection system can be stabilized at about 20,000. At any number of threads, the system pressure will increase dramatically with the increase in the number of analog connections. The music recognition algorithm based on DL and hash method discussed is of great significance in improving the classification accuracy of music recognition. The application of blockchain technology in the copyright protection platform of original music works can protect the copyright of digital music and ensure the operation performance of the system.

Methodological Approach for Identifying Websites with Infringing Content via Text Transformers and Dense Neural Networks

“…In the realm of safeguarding digital assets, twenty-three significant research works [6,7,19,23,[25][26][27][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63] have been identified. Of these, nine [6,7,19,23,[25][26][27][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63] focus on the use of legal resources and partially address technical aspects. Ten of these works [25,26,[53][54][55]…”

“…Blockchain Integration [63] This refers to schemes using AI, ML, and Blockchain to synthesize multimedia files, producing hashes of multimedia databases and catalogs. This facilitates a comparison between the original and infringing files by identifying alterations or removals of metadata or protections, like fingerprinting and watermarking.…”

“…These are designed to safeguard multimedia works by digitally enforcing copyright laws. -AI/ML-driven protection [27,[61][62][63] is an intelligent scheme that utilizes one or more AI/ML models to enhance the protection of multimedia objects in the IoE, in conjunction with non-technical or technical processes.…”