Real-Time Vocal Characteristic Parameter Evaluation Method Based on Future Network

This paper proposes a real-time vocal feature parameter evaluation method that integrates edge computing and future network technology to address the application needs of automatic evaluation in vocal practice and singing. This method first uses sensors to measure real-time feature parameters such as pitch accuracy, rhythm, and intensity of the original singing voice, and matches and compares them with standard parameters. With the low latency and high bandwidth characteristics of future networks, the collected data can be quickly transmitted to the cloud or a local processing unit for analysis. Simulation experiments and application results show that the algorithm complexity of this method is low, the scoring time is fast, and its scoring results are consistent with human subjective evaluation at 97.2%. The advanced features of future networks will provide strong support for efficient data transmission and processing, bringing new technological breakthroughs and application prospects to the field of vocal evaluation.