Exploration of the Integration of Traditional Music Cultural Elements in Music Informatization Teaching

Abstract

Abstract With the development of information technology, music teaching methods are getting more affluent and more prosperous. This paper proposes a model for emotion classification and assessment that integrates traditional music culture elements with information technology in music teaching. The research first combines TextCNN and BiLSTM algorithms to establish the emotion classification model of conventional music. Then it combines PYIN and DTW algorithms to establish the evaluation model of traditional music, which completes the auxiliary efficacy of music informationized teaching. In the emotion classification test of the model, the classification accuracy and F1 value of emotions of different music samples are 82.98% and 75.22%, respectively. The model’s recognition accuracy of the four voices is 86.76%, and the overall effective scoring percentage is 81.98% under different playing abnormalities. This study has had an impact on traditional music evaluation. The model in this paper can be used to classify and evaluate emotions in conventional music, providing more intelligent and high-quality technical services for integrating traditional music into music teaching.