The analysis of Chinese National ballad composition education based on artificial intelligence and deep learning

This study focuses on generating national ballads with ethnic characteristics through algorithms, and exploring the application of artificial intelligence in music composition. As an important component of Chinese traditional culture, national ballads carry rich emotions and historical significance. However, due to the complexity and artistry of their creation process, traditional manual composition faces certain limitations. To address this, the study proposes a music composition model based on the combination of the Markov chain (MC) and Bidirectional Recurrent Neural Network (Bi-RNN). The model aims to generate melodies and emotional expressions that align with the style of ethnic national ballads. This method uses the MC to generate the basic framework of the melody, and adopts the Bi-RNN to further optimize rhythm and emotional expression. Experimental results show that, compared to traditional manual composition and the MC approach in music computing, the proposed method has significant advantages in melody creation and emotional expression. Besides, it can generate music that is consistent with ethnic styles. This study provides a new approach and method for the application of artificial intelligence in music composition, which has important implications for music education and cultural heritage preservation.