(In development) a Music Pattern Detector that combines formal language theory with computational musicology.

Implemented a finite automata-based progression recognition engine using the Aho-Corasick algorithm to efficiently detect harmonic and rhythmic structures in symbolic music.

Designed the system for genre detection by associating genres with characteristic progression grammars.

Future extensions include integrating deep learning models (CNNs, RNNs, Transformers) to process raw audio input and extract symbolic features directly from waveforms, enabling a hybrid rule-based + neural network architecture for scalable music analysis and classification.