Intellectual Property India Publishes Patent Application for “ragalchemy: A Modular Artificial Intelligence System For Generating Midi Files From Indian Classical Music Inputs”

MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202621054470 A) filed by Tejashri Kolhe on April 29, 2026, for “ragalchemy: A Modular Artificial Intelligence System For Generating Midi Files From Indian Classical Music Inputs”.

Inventors include Tejashri Kolhe; Purva Pawar; Devanshu Manchekar; Samarth Lokhande; Soham Kalolikar; and Dr. Mahesh Pawaskar.

The application for the patent was published on June 26, 2026, under issue no. 26/2026.

Abstract: ABSTRACT: The present invention i.e “RAGALCHEMY: A Modular Artificial Intelligence System for Generating MIDI Files from Indian Classical Music Inputs” discloses a system and method for automated generation of structured musical output in the form of a MIDI file based on user-defined parameters and rule-based intelligent processing. The system comprises six distinct modules operating in a sequential pipeline. A User Input Module captures input parameters including raga selection, tempo, instrument type, and beats per minute. A Processing and Validation Module verifies the integrity, consistency, and permissible bounds of the provided inputs based on predefined musical and system constraints. An AI-ML Processing Module analyzes validated inputs using rule-based and/or trained models to derive context-aware musical characteristics, without directly generating note sequences. A Swara Sequence Generation Module subsequently constructs a structured sequence of swaras (notes) in accordance with the analyzed parameters and raga-specific rules. A MIDI Encoding Engine converts the generated swara sequence into standardized MIDI format by mapping musical attributes to digital encoding protocols. Finally, an Output Module produces a downloadable MIDI file corresponding to the encoded sequence. Each module performs a distinct and non-overlapping function, ensuring clarity in processing stages and modular independence within the system. The proposed system ensures a clear separation of functional responsibilities across modules, thereby improving interpretability, scalability, and reproducibility of the musical generation process. By integrating validated user inputs with intelligent analytical processing and structured sequence generation, the invention enables efficient transformation of classical music parameters into standardized digital audio outputs, while maintaining adherence to defined musical frameworks.

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