Harmonizing Sounds: A Comprehensive Approach to Automated Music Transcription and Vocal Isolation
Kevin S. Paul, Junaid Basha, Indrajit Karmakar, Vishnu Konar, S Rizwana · 2024
The development of an automated music transcription system represents a pivotal advancement in the domain of music technology, catering to diverse needs across musical education, production, research, and accessibility. This paper underscores the significance of such a system in preserving musical heritage, facilitating learning, fostering collaboration, and enhancing efficiency in transcribing music. Through an extensive review of existing literature, the paper examines various approaches and limitations in automated music transcription. Leveraging insights from prior work, the paper proposes a comprehensive model aimed at accurately converting audio recordings into sheet music or symbolic representations, while also incorporating functionalities such as vocal isolation and lyrics generation.