<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">EIR</journal-id><journal-title-group><journal-title>Educational Innovation and Research</journal-title></journal-title-group><issn>3066-8298</issn><eissn>3066-828X</eissn><publisher><publisher-name>Art and Technology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/EIR.2026070013</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>AI辅助工具在高校美声基础教学中的应用实践</title><url>https://artdesignp.com/journal/EIR/2/7/10.61369/EIR.2026070013</url><author>张凝</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>2</volume><issue>7</issue><history><date date-type="pub"><published-time>2026-07-20</published-time></date></history><abstract>在人工智能技术飞速发展的今天，AI辅助教学正在逐渐向大学声乐教学中渗透。传统美声教学的评价体系长期以教师的主观听觉判断为核心依据，尚未建立起统一规范的客观量化标准，这使得评价结果不可避免地受到教师个人教学经验、审美偏好与艺术取向的影响。与此同时，我国高校声乐教育领域的实际教学中，普遍存在教师的教学科研与育人能力协同发展仍不均衡，专业综合素养亦存在进一步提升的空间的情况。本文以我国高校美声基础课为研究对象，针对长期以来在声乐基础教学中反馈滞后、主客观评价不均衡等结构性问题，通过文献调研和教学实践观测等方法，对语音语调矫正、呼吸训练、共鸣调整和咬字吐字四个核心教学环节的应用场景和技术实现路径进行系统性的梳理。研究表明，人工智能在基本技能培训方面具有明显优势，可将音高反馈时间缩短到毫秒级，并可直观地显示呼吸和共振状态。据此，本文提出&amp;ldquo;以技术支持取代替代&amp;rdquo;的核心价值观，建立&amp;ldquo;课前AI预习-课堂师生协作-课后数据驱动&amp;rdquo;的闭环教学模型，为美声唱法的数字化改造奠定理论和实践基础。</abstract><keywords>人工智能,美声唱法,基础教学,辅助工具,声乐教育</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] 白钰. 高校音乐教育专业声乐教学质量提升策略&amp;mdash;&amp;mdash; 基于&amp;ldquo;三教&amp;rdquo;改革背景[J]. 大观（论坛），2024(3):148-150.[2] 滕腾.AI 辅助音乐教育&amp;ldquo;新质&amp;rdquo;教学应用研究[J].中国音乐，2025(4):137-146.[3] 齐婷婷，张义民. 基于功率谱的美声发声特征提取[J]. 振动、测试与诊断，2023，43(6):1187-1192.[4]Chen L, Xu Y. Study on the Design of an AI-Based Singing Training System Using Feature Comparison[C]//Proceedings of the 2025 International Conference on Multimediaand Artificial Intelligence. ACM, 2025: 123-129.[5]Xiao H.Using Artificial Intelligence Software for Correcting Incorrect Intonation in Singing [J].Journal of Theoretical and Applied Information Technology，2025，103(6):2313-2320.[6]Liu H, Guo W. Effectiveness of AI-Driven Vocal Art Tools in Enhancing Student Performance and Creativity [J]. European Journal of Education, 2025, 60 (1): e70037. DOI:10.1111/ejed.70037.[7]唐晓敏.AI 技术在音乐艺术创造教学中的应用[J].人像摄影，2025(11):174-176.[8]Yap J H. The Challenges and Issues in Artificial Intelligence (AI) in Vocal Performance Education: A Comprehensive Narrative Review [J]. International Journal of Researchand Innovation in Social Science, 2025, 9 (10): 4691-4696.[9]Zou Y, Wang H. TimbreSense: Timbre Abnormality Detection for Bel Canto with Smart Devices [J]. IEEE Access, 2024, 12: 45678-45689.[10] 韩星冉.AI 视域下高校音乐通识教育教学改革: 困境, 前景与路径[J].黑龙江高教研究，2025，43(11):144-150.[11]Yan T, Yu H. Integration of AI Technology into Vocal Music Education: An Investigation of Teachers&amp;rsquo; Attitudes in Higher Education in Guangdong, China [J]. InternationalJournal of New Developments in Education, 2026, 8 (3): 1-11. DOI: 10.25236/IJNDE.2026.080301.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
