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From Notes to Keys: A VR Learning Environment for Sheet Music Interpretation

  • Sandeep Khanna
  • , Atanu Saha
  • , Rahul Kumar Ray
  • , Rakesh Patibanda
  • , Chiranjoy Chattopadhyay

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Learning to interpret sheet music and play musical instruments (piano) remains a significant challenge for beginners, often requiring extensive practice and guidance. Existing platforms lack real-time feedback and seamless sheet music interpretation, creating inefficiencies that require a system for accurate note recognition, intuitive guidance, and reduced cognitive load. To address this, we propose a novel system that integrates optical music recognition (OMR) and virtual reality (VR) to create an immersive piano learning environment. The proposed approach improves the detection of musical notes by making it scale and rotation invariant. The detected notes are converted into the corresponding piano keys and sequential instructions. These instructions are then visualized in a VR environment in Meta Quest 3, where a virtual piano highlights keys dynamically to guide the user. The experimental results demonstrate high accuracy in note detection and significant improvements in the learning curve for beginners, reducing cognitive load, and bridging the gap between sheet music interpretation and piano playing. This work highlights the potential of combining document image analysis and VR technologies to revolutionize music education, as well as other related fields, offering a scalable and accessible solution.

Original languageEnglish
Title of host publicationDocument Analysis and Recognition – ICDAR 2025 - 19th International Conference Wuhan, China, September 16–21, 2025 Proceedings, Part III
EditorsXu-Cheng Yin, Dimosthenis Karatzas, Daniel Lopresti
Place of PublicationCham Switzerland
PublisherSpringer
Pages22-39
Number of pages18
ISBN (Electronic)9783032046246
ISBN (Print)9783032046239
DOIs
Publication statusPublished - 2026
EventInternational Conference on Document Analysis and Recognition (ICDAR) 2025 - Wuhan, China
Duration: 16 Sept 202521 Sept 2025
Conference number: 19th
https://link.springer.com/book/10.1007/978-3-032-04624-6 (Proceedings)
https://www.icdar2025.com/ (Website)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume16025
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Document Analysis and Recognition (ICDAR) 2025
Abbreviated titleICDAR 2025
Country/TerritoryChina
CityWuhan
Period16/09/2521/09/25
Internet address

Keywords

  • Document Recognition
  • Immersive Learning
  • Music Education
  • Optical Music Recognition
  • Symbol spotting
  • Virtual Reality

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