Direct Visualization of Bass Guitar Frequency Patterns and Their Fret Fingerings via Combined Fast and Short-Time Fourier Transforms

Jungmin Lee, Won Gu Lee

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: This study aims to develop an efficient method for transcribing bass guitar notes from polyphonic music, addressing the challenges in creating user-friendly tablature for low-frequency instruments. Methods: Employing Fast Fourier Transform (FFT) and Short-Time Fourier Transform (STFT), the method divides music into sections to extract bass notes, identifying frequencies using FFT with Hamming windowing and isolating fundamental frequencies. STFT and image recognition determine note details, such as lengths, and Euclidean methods with minimum distance estimation are used to generate tablatures reflecting minimal finger movements. Results: Findings show a Word Error Rate (WER) of 3.13% and a Character Error Rate (CER) of 6.25% in simple polyphonic music, demonstrating the method's effectiveness. Challenges remain in transcribing complex compositions, indicating a need for methodological refinement. Conclusion: The research proposes a simple and effective transcription method for bass guitar from polyphonic music, generating tablatures that assist amateurs in performing more easily. It opens avenues for further improvement in automatic music transcription technologies and suggests potential applications in detecting mechanical faults in low-frequency domains.

Original languageEnglish
JournalJournal of Vibration Engineering and Technologies
DOIs
Publication statusAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2024.

Keywords

  • Fast Fourier transform (FFT)
  • Fundamental frequency
  • Music transcription
  • Short-time Fourier transform (STFT)
  • User-friendly tablature

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