
Atharv D. 2025 | BASIS Independent Fremont
- Project Title: AI-Powered Tabla Accompaniment for Indian Classical Music with Convolutional Neural Networks (CNNs) and Real-Time Signal Processing
- BASIS Independent Advisor: Dr. Dixit
Indian Classical Music relies heavily on the intricate interplay between vocalists and accompanying instruments such as the tabla. However, live accompaniment is often challenging or altogether impossible to arrange for practice and performance. This lack of consistent accompaniment limits musicians’ opportunities to perfect their skills, experiment with improvisations, and develop rhythmic fluency. Musicians today lack robust tools to address this need, and current technologies fall short in providing responsive, real-time accompaniment that authentically mirrors a human musician’s adaptive qualities. This project aims to develop an AI-powered system that provides real-time tabla accompaniment, filling an important void in music technology by offering Indian classical musicians, particularly vocalists, an AI-driven tabla accompaniment tool that closely resembles human responsiveness. I will start by gathering musical samples, proceed to train a Convolutional Neural Network (CNN) to generate rhythms overlaid on pre-recorded samples, extend this process to work in real-time, and finish with a fully functional model capable of responding dynamically to a live performer’s tempo and improvisation.