The purpose is to coordinate the relationship between innovation and entrepreneurship education (IEE) and professional education. This exploration is based on the entrepreneurial spirit of young entrepreneurs and the re-integration of IEE and music education in colleges. First, the IEE is studied in theory. Then, the basic criteria for integrating IEE and professional education are studied, and 305 students from a music college in Xi’an are taken as the survey sample. The questionnaire is adopted to investigate the current situation of the integration of IEE and professional education. The results show that 52.1% of students believe that IEE is closely related to professional education. In terms of self entrepreneurship awareness, males’ awareness of self entrepreneurship is higher than females’, and the willingness of self entrepreneurship from freshman to senior is 3.1, 15.5, 26.1, and 30.8%, respectively. For the dominant position in the integrated curriculum, 55.6% hold that professional courses should dominate innovative professional courses, and 25.9% believe that innovation and entrepreneurship courses should be dominated. Besides, 16.5% think that the proportion of the two should be the same, and 2% hold that it doesn’t matter. For the enthusiasm of innovative professional courses, only 14.1% of students are very positive. The survey results show that the integration of IEE and professional education needs to be improved, and there is a lack of pertinence and guidance for students of different genders and grades. Students are not clear about the position of IEE and lack enthusiasm. Finally, reasonable suggestions are put forward in view of the above problems. The results are conducive to promoting and accelerating the process of talent training mode combining professional education and IEE. It has a certain reference value for college education and teaching reform.
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.
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