Title

ReCHORD: a hardware interface for algorithm-based chord recognition

Date of Publication

2016

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science

Subject Categories

Programming Languages and Compilers

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Clement Y. Ong

Defense Panel Chair

Jocelyn W. Cu

Defense Panel Member

Dr. Rafael A. Cabredo
An Franchesca B. Laguna

Abstract/Summary

Chord recognition today continues to suffer from low accuracy with complex chords, with the majority of implementations relying, mostly on software alone. The music information retrieval evaluation exchange (MIREX), which has entries focused on software-based chord recognition. In MIREX 2015 for example, the latest algorithms presented for chord recognition resulted in 43.82% to 82.20% for basic chords, and 17.04% to 76.04% for complex chords. On the other hand, an approach using stereo cameras achieved an accuracy of 98.4%, though the system outputs a chord even if the sound produced is incorrect or none is produced at all, as long as the finger position is correct.

In this research, a real-time chord detection system was built to recognize basic and complex chords from a guitar. With the use of a custom-built individualized string pickup, processing of a very complex signal due to the summation of all the signals from the 6 strings of the guitar would not be needed anymore. The software tailored for the hardware achieved 100% accuracy for note recognition and single-play chord recognition, and 91% continous-play chord recognition with the tempo slower than the temporal resolution of the system. The range of chords that were tested include major, minor, diminished, augmented, major 7th, minor 7th, diminished 7th, dominant 7th, suspended 2nd, and suspended 4th. With the Arduino as the microcontroller interface and all the software delay, a temporal resolution of around 2.2 seconds for the system is achieved.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU18971

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

1 volume (various foliations): illustrations (some color) ; 29 cm.

Keywords

Chords (Music) -- Data processing; Guitar -- Chord diagrams -- Data processing

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