用AI和音频分析自动从视频生成吉他谱，提升教学与转录效率
TapToTab : Video-Based Guitar Tabs Generation using AI and Audio Analysis
- 用YOLO模型实时检测吉他指板位置
- 结合傅里叶变换精准识别音符，准确率显著提升
- 适合音乐教育者、自学吉他者及乐谱自动化研究者
从视频输入自动生成吉他谱具有巨大潜力，可提升音乐教育、转录准确性和表演分析水平。现有方法在指板检测和音符识别的一致性与完整性方面存在挑战。本文提出一种先进方法，结合深度学习技术：使用YOLO模型实现指板的实时检测，并通过基于傅里叶变换的音频分析实现音符的精确识别。实验结果表明，该方法在检测精度和鲁棒性方面相比传统技术有显著提升。本文详细阐述了该方法的开发、实现与评估，旨在通过自动化视频到吉他谱的转换，革新吉他教学方式。
原文摘要 · Abstract (English)
The automation of guitar tablature generation from video inputs holds significant promise for enhancing music education, transcription accuracy, and performance analysis. Existing methods face challenges with consistency and completeness, particularly in detecting fretboards and accurately identifying notes. To address these issues, this paper introduces an advanced approach leveraging deep learning, specifically YOLO models for real-time fretboard detection, and Fourier Transform-based audio analysis for precise note identification. Experimental results demonstrate substantial improvements in detection accuracy and robustness compared to traditional techniques. This paper outlines the development, implementation, and evaluation of these methodologies, aiming to revolutionize guitar instruction by automating the creation of guitar tabs from video recordings.
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