Guitar Music Transcription (GMT)
Date of Publication
2009
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Rafael Cabredo
Defense Panel Member
Jocelyn Cu
Karlo Campos
Abstract/Summary
Existing systems for regular music transcription are limited to external information for accurate transcriptions. An example of this is the use of midi file formats along with guitar synthesizers and a format that can store additional music information. The output of this research is a prototype for an application tool that handles the basic issues of music transcription. The tool lessened transcription inaccuracies by using feature extraction techniques that can detect and distinguish notes more accurately. The features that the research focused on are the pitch and duration of the note. To compute the basic music features the following approach were implemented: onset detection using edge detection filter frequency estimation using fast Fourier transform duration estimation using a histogram and assigning a note value to the most current note and note classification. All manipulated features are passed to the system's interpreter, which is then formatted to MusicXML file format. The prototype has an accuracy of 97% for pitch detection and 79% for note duration estimation.
Abstract Format
html
Language
English
Format
Accession Number
TU19861
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1 v. (various foliations) leaves : 28 cm. + one computer optical disc.
Keywords
Arrangement (Music)
Recommended Citation
Chua, E. S., Hernandez, R. C., Lautchang, W. J., & Ong, R. T. (2009). Guitar Music Transcription (GMT). Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/5939