Please use this identifier to cite or link to this item:
Title: Study of pitch detection for musical instruments
Authors: Tay, Eileen Kia Khee
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: There are multiple researches on pitch detection and many of them are successful. However, detecting multiple pitches and identifying the names of the pitch combination proved to be a challenge. Current researches on chord detection are able to identify simple and commonly used chords. Nevertheless, there are still room for improvement to identify complex chords. Hence, this project looked into ways to produce an algorithm such that it can perform chord detection accurately on the various complexities of chords. It aims to provide an accurate estimation of the chords played by the piano. Guitar will also be used to determine the algorithm’s reliability in detecting chords played by other instruments. The algorithm is compared with other current chord detector software, Chordata and Musical Friend, in detecting various complexities of chords. Based on the results of this project, the algorithm has proven to be able to accurately identify most of the chords, including those with high complexities. However, there is still room for improvement such that all chords can be accurately identified.
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Final Report_U1520758A.pdf
  Restricted Access
1.48 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 20, 2024


Updated on Jun 20, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.