Optimization of Vocal Teaching Empowered by AI A Comprehensive Study on Quantitative Evaluation and Personalized Guidance System for Singing Skills Based on Voiceprint Feature Extraction
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Abstract
The integration of artificial intelligence into vocal education provides new opportunities for overcoming limitations associated with subjective assessment and insufficient personalized guidance. This study proposes an AI-enabled vocal teaching framework based on voiceprint feature extraction and intelligent evaluation. Acoustic features including pitch, timbre, rhythm, and spectral characteristics are extracted through a multi-stage signal-processing pipeline, while machine-learning models are employed to establish quantitative singing-skill evaluation mechanisms. Based on diagnostic results, a personalized guidance module generates adaptive training recommendations for individual learners. Experimental analysis demonstrates that the proposed framework effectively improves evaluation consistency, enhances training efficiency, and supports individualized skill development. The study contributes to intelligent vocal education and provides methodological references for speech signal processing, acoustic pattern recognition, and intelligent human–computer interaction systems.
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References
C. Peng, “A Personalized Recommendation Method for Vocal Music Teaching Resources Based on Network Topology,” International Journal of High Speed Electronics and Systems, vol. 35, no. 03, 2025, doi: 10.1142/S012915642540467X.
F. Bin, “Exploration of the Integration of Singing Techniques and Artistic Expression in Vocal Teaching,” Adult and Higher Education, vol. 7, no. 1, 2025, doi: 10.23977/ADUHE.2025.070107.
Z. Zhang, “The Teaching Method of STEAM Education-based Audio-visual Aesthetics in College Vocal Music Teaching,” Frontiers in Educational Research, vol. 8, no. 2, 2025, doi: 10.25236/FER.2025.080216.
W. Wang, “Analysis of the Transformation Path of Digitally Empowered Vocal Music Teaching in Colleges and Universities,” Exploration of Educational Management, vol. 3, no. 2, 2025, doi: 10.12417/3029-2328.25.02.008.
Z. Zhina, “Research on the application and teaching practice of ‘thirteen Zhe’ in Chinese art songs,” The Art & Design Research, vol. 6, no. 1, 2025, doi: 10.37420/J.ADR.2025.006.
Y. Cheng, “The Significance of Chinese Original Vocal Music for the Development of Chinese Ethnic Vocal Music,” Education Research and Innovation, vol. 1, no. 2, 2025, doi: 10.62639/SSPERI02.20250102.
L. Qin, “Research on Vocal Teaching under the Perspective of Multicultural Nationalities,” Education Research and Innovation, vol. 1, no. 2, 2025, doi: 10.62639/SSPERI05.20250102.
Z. Hu, “Research on Interactive Content Development of Vocal Music Teaching in College Music Courses in the New Media Era,” Applied Mathematics and Nonlinear Sciences, vol. 10, no. 1, 2025, doi: 10.2478/AMNS-2025-0029.
M. Wang and H. Wang, “Research on Diversified Innovative Paths of Vocal Music Teaching in College Music Education Promoted by Information Technology,” Applied Mathematics and Nonlinear Sciences, vol. 10, no. 1, 2025, doi: 10.2478/AMNS-2025-0638.
X. Huang, “The Optimization of Strategies for Precision Teaching Reform of Vocal Music Education in Colleges and Universities in the Framework of Information Technology,” Applied Mathematics and Nonlinear Sciences, vol. 10, no. 1, 2025, doi: 10.2478/AMNS-2025-0679.
Y. Chen, “Analysis of the Reform of Vocal Music Teaching by Using Network Platform in the New Media Era,” Lecture Notes in Electrical Engineering, pp. 747-754, 2022, doi: 10.1007/978-981-19-4775-9_96.
M. Moreno and E. Woodruff, “Exploring the Effects of Background Music on Real-Time Emotional Expressions, Performance, and Confusion Mediation in Middle School Students,” Technology, Knowledge and Learning, vol. 28, no. 1, pp. 143-163, 2023, doi: 10.1007/s10758-021-09556-9.
Z. Sun, “The Reform of Vocal Music Education in Universities Under the Concept of Innovation,” Contemporary Education and Teaching Research, vol. 5, no. 12, 2024, doi: 10.61360/BoniCETR242017251203.
Y. Zhu, “Discussion on the Application of Innovative Teaching Methods in the Vocal Course of Middle and High Preschool Vocational Education Majors,” Educational Innovation Research, vol. 2, no. 2, pp. 92-97, 2024.
J. Zheng, Y. Zhang, and S. Zhang, “Audio-visual aesthetic teaching methods in college students’ vocal music teaching by deep learning,” Scientific Reports, vol. 14, no. 1, 2024, doi: 10.1038/s41598-024-80640-7.
F. Bin, “Innovation and Practice of Vocal Teaching Mode in Digital Environment,” Curriculum and Teaching Methodology, vol. 7, no. 8, 2024, doi: 10.23977/CURTM.2024.070828.
M. Hu, “Research on the Value and Path of Family Art Education-Take Vocal Music Education as an Example,” Journal of Research in Vocational Education, vol. 6, no. 10, pp. 43-47, 2024, doi: 10.53469/JRVE.2024.6(10).08.
X. Wenyi and W. Decai, “Research on the employment dilemma and path of college vocal music graduates,” Adult and Higher Education, vol. 6, no. 7, 2024, doi: 10.23977/aduhe.2024.060709.
Q. Du, “A Systematic Approach to Innovative Strategies for Vocal Instruction in Higher Education: Enhancing Student Performance,” Pacific International Journal, vol. 7, no. 5, 2024, doi: 10.55014/PIJ.V7I5.696.
R. Schutz, Welsh Vocal Music: A Guide to Lyric Diction and Repertoire. London, U.K.: Taylor & Francis, 2024, doi: 10.4324/9781003347347.