TapToTab: Video-Based Guitar Tabs Generation Using AI and Audio Analysis

Ghaleb, Ali; Elsadawy, Eslam; Essam, Ihab; Zaky, Seif Eldin; Abdelhakim, Mohamed; Fahim, Natalie; Bayoumi, Razan; Hanan Hindy;

Abstract


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.


Other data

Title TapToTab: Video-Based Guitar Tabs Generation Using AI and Audio Analysis
Authors Ghaleb, Ali; Elsadawy, Eslam; Essam, Ihab; Zaky, Seif Eldin; Abdelhakim, Mohamed; Fahim, Natalie; Bayoumi, Razan; Hanan Hindy 
Keywords Audio-visual Integration;Automated Guitar Transcription;Canny Edge Detection;Computer Vision;Deep Learning;Fourier Transform;Frequency Analysis;Fretboard Detection;Guitar Tablature Generation;Image Processing;Real-time Performance Analysis;YOLO
Issue Date 1-Jan-2024
Conference 4th International Mobile Intelligent and Ubiquitous Computing Conference Miucc 2024
ISBN [9798350367775]
DOI 10.1109/MIUCC62295.2024.10783648
Scopus ID 2-s2.0-85216127123

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