A Study on the Utilization of Polyphonic Folk Songs in College Choral Teaching in the Context of Big Data

Abstract

Introducing polyphonic folk songs into the choral teaching classroom in colleges and universities not only helps to carry forward the excellent traditional culture but also promotes the students’ emotional education and physical and mental health development. This paper analyzes the status quo and dilemma of the use of polyphonic folk songs in college choral teaching and puts forward the model of music choral intelligent tutoring system (ITS) and the method of spectral tone recognition as countermeasures. A collaborative filtering algorithm is used to construct the learning resource recommendation algorithm in the music chorus intelligent guided learning system model, which is based on the ITS system structure. The YIN algorithm is used to extract the audio, and the pitch template matching is accomplished with the help of the improved DTW algorithm to complete the choral ability assessment. An improved normal harmonic algorithm has been proposed to preprocess the audio signal and achieve spectral tone recognition for multi-part folk songs in the fundamental frequency extraction stage of spectral tone recognition. In a comprehensive university in Sichuan Province, China, the teaching practice of polyphonic folk song chorus was carried out. The students’ scores in the dimensions of learning interest and learning confidence increased by 0.976 and 0.698 on average after the experiment. The p-values were all less than 0.05, showing significant differences.

Keywords

• its system
• collaborative filtering algorithm
• yin algorithm
• dtw algorithm
• fundamental frequency extraction
• normal harmonic algorithm
• choral teaching
• 62-07