AI-POWERED BEAT DETECTION AND ITS EDUCATIONAL USES

Authors

  • Manish Gudadhe Department of Computer Science & Engineering (Data Science), St. Vincent Pallotti College of Engineering and Technology, Nagpur, India
  • Gunveen Ahluwalia Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
  • Prince Kumar Associate Professor, School of Business Management, Noida international University 203201
  • Ansh Kataria Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
  • Dr. Ronald Doni A Associate Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India
  • Ms. Hanna Kumari Assistant Professor, Department of Interior Design, Parul Institute of Design, Parul University, Vadodara, Gujarat, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6627

Keywords:

AI Beat Detection, Audio Signal Processing, Machine Learning in Music, Neural Networks, Music Education, Interactive Learning

Abstract [English]

AI powered beat recognition is a huge step forward in audio signal processing since it brings together the power of machine learning and the intricate rhythms of music. Earlier methods for the search of beats were based on energy analysis of the signal and frequency decomposition, which were many times limited by the variation of the pace, the type and the quality of the recordings. Nowadays, deep learning has led to the ability of computer systems to learn rhythmic patterns from large datasets. This allows beats to be found in a much greater variety of musical styles more accurately and adaptively. Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) work with the data particularly well because they extract out the hierarchical time patterns as well as finds relationships between events in audio data. The effects this technology will have on the way we teach are huge. AI-driven beat recognition in music classes helps to improve rhythm training by providing students with feedback in real time in order to help them improve their timing and rhythmic awareness. In addition to the normal means of teaching music, AI beat recognition enables interesting learning tools and games with rhythm, as well as virtual instruments that change according to the action of the user. These systems promote engagement in both the online and school environments through learning environments that are both flexible and personalized with feedback and apps that tie music and math to cognitive science. Case studies show that platforms with AI beats recognition make learning more fun, keeps students motivated and helps them to understand the rhythmic ideas.

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Published

2025-12-10

How to Cite

Gudadhe, M., Ahluwalia, G., Kumar, P., Kataria, A., Doni A , R., & Kumari, H. (2025). AI-POWERED BEAT DETECTION AND ITS EDUCATIONAL USES. ShodhKosh: Journal of Visual and Performing Arts, 6(1s), 457–467. https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6627