Cited By
View all- Jadhav YPatel AJhaveri RRaut R(2022)Transfer Learning for Audio Waveform to Guitar Chord Spectrograms Using the Convolution Neural NetworkMobile Information Systems10.1155/2022/85447652022Online publication date: 1-Jan-2022
Automatic Guitar Music Transcription
Pages 197 - 202
Abstract
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.
- Automatic Guitar Music Transcription
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Published In
November 2012
531 pages
ISBN:9780769549590
Publisher
IEEE Computer Society
United States
Publication History
Published: 26 November 2012
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Cited By
View all- Jadhav YPatel AJhaveri RRaut R(2022)Transfer Learning for Audio Waveform to Guitar Chord Spectrograms Using the Convolution Neural NetworkMobile Information Systems10.1155/2022/85447652022Online publication date: 1-Jan-2022
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