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

TL;DR

This paper presents a novel AI-based system that automatically generates guitar tabs from videos by combining real-time fretboard detection with audio note analysis, improving accuracy and robustness over traditional methods.

Contribution

It introduces a deep learning approach using YOLO for fretboard detection and Fourier Transform for note identification, advancing automated guitar tab generation from video.

Findings

Enhanced detection accuracy over traditional methods

Robustness in various video conditions

Effective note identification from audio signals

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.