Exploring the Diversified Development of Vocal Music Teaching Methods in Colleges and Universities Combined with Multi-Priority Dynamic Threshold Algorithm

Abstract

Abstract Enhancing the integration of modern information technology with educational practices, particularly in the vocal classroom, is crucial for improving academic quality. This paper presents an optimization method aimed at addressing the limitations of the existing multi-priority dynamic threshold algorithm. The specific performance is as follows: first, on the original basis of the PDT-RED algorithm, the expected cache utilization is set to ensure the utilization of the buffer. The optimized OPDT-RED algorithm should be used to ensure that the data frame is received with a high probability. Then, according to the channel environment, the dynamic fullness threshold was adjusted, which improved the performance of the highest priority queue with a high transmission success rate. Lastly, the measurements of vocal characteristic parameters like pitch, rhythm, beat, melody, and others. The goal was to create a complete evaluation network model for vocal teaching, which was applied to actual cases. The model’s performance and its effectiveness were evaluated. After testing, the subjects’ vocal rhythmic tempo was below 60, while the range of the sample repertoire was between 60 and 90, presenting two different forms of expression. The model proposed in this paper has the optimal effect on the enhancement of expressive movements while singing; 15.33% of the students improved by two notches, and the vocal teaching model designed in this paper has a very good effect on vocal enhancement.