Publication Type : Conference Paper
Publisher : IEEE
Source : 2024 5th IEEE Global Conference for Advancement in Technology (GCAT)
Url : https://doi.org/10.1109/gcat62922.2024.10924127
Campus : Bengaluru
School : School of Computing
Department : Computer Science and Engineering
Year : 2024
Abstract : The Music Analyzer project is a musician-friendly tool that improves chord analysis and identification. It uses finite automata and Python to process MIDI (Musical Instrument Digital Interface) files created from BandLab recordings in an efficient manner. By utilizing Finite State Machines, it quickly recognizes chords on input, and enables musicians to easily learn and play along by breaking down key signatures and creating major and minor scales. The system’s user-friendly interface promotes the mastery of complicated compositions by musicians by offering clear outputs. This software makes music analysis easier, making it suitable for both practice and performance, enhancing the musical experience.Testing with a variety of chords and playing styles confirmed the system’s accuracy and responsiveness. The Music Analyzer consistently provides quick and precise chord recognition. The system successfully identified chords from real-world recordings in BandLab Studio, demonstrating its effectiveness in handling complex musical compositions.
Cite this Research Publication : Konjarla Sripriya, Likhitha Sri Kandukuri, S Ajay Ratnam, Singadi Srujan Reddy, Niharika Panda, Dynamic Chord Identification using Finite State Machines, 2024 5th IEEE Global Conference for Advancement in Technology (GCAT), IEEE, 2024, https://doi.org/10.1109/gcat62922.2024.10924127