Musical Chords Recognition System Using Artificial Intelligence Techniques
Keywords:
Music Chords Recognition, AI-Powered System, NNLS Chroma Algorithm, Audio Input Recognition, Music TechnologyAbstract
In response to the evolving landscape of music creation and technology, the ChordWizard AI-powered Music Chords Recognition Web System addresses the challenges of accurately recognizing music chords. The primary objective is to develop and evaluate the effectiveness of ChordWizard in improving music chord recognition. The project examines modules such as Register and Login, Audio Input Recognition, Music Theory, MIDI File Sharing, Forum, Update Profile, and Administrative Tasks. Utilizing the advanced NNLS Chroma algorithm, Python Audio and chords libraries, and the Linux operating system, the system ensures precision and reliability. Key findings show that ChordWizard significantly improves the accuracy and speed of music chord recognition. The Audio Input Recognition module effectively understands diverse musical compositions, from single instruments to genres like pop, classical, and EDM. These results highlight the transformative potential of ChordWizard in music technology, addressing current challenges and paving the way for future enhancements. Future research may explore AI advancements for creating original chord compositions across different music genres.



