Automatic guitar music transcription

• Main Authors: Alcabasa, Lance, Marcos, Nelson
• Format: text
• Published: Animo Repository 2012
• Subjects: Music—Data processing; Guitar music—Data processing; Signal processing; Computer Sciences; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2146; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3145/type/native/viewcontent
• Institution: De La Salle University

This paper presents a system that helps in automatically generating guitar tablatures and musical scores based on musical audio data. Information gathered from the audio consists of pitch, onsets and durations, chords, and beat and tempo. Major issues that were encountered during the research were harmonics for pitch detection, thresholding for onset detection, chord distinction, similar chord structures for chord labeling, and the subjective quality of tempo. Results were generally acceptable, performed on a data set that contains 22 files with varying elements. 70% accuracy was gathered from pitch detection, 60% accuracy from onset detection, 86% accuracy for chord distinction, 85% accuracy for chord labeling, and 81% accuracy for beat and tempo. © 2012 IEEE.