Automatic Music Transcription (AMT) remains a challenging task in music information retrieval (MIR), particularly for polyphonic piano music where multiple notes overlap in time and frequency. This paper presents Piano2Notes , an end-to-end modular system that converts raw piano audio into structured digital notation (MIDI and staff notation). The system combines classical digital signal processing (DSP) for onset detection with a convolutional recurrent neural network (CRNN) for multi-pitch estimation, followed by a Hidden Markov Model (HMM) for note tracking. We evaluate Piano2Notes on the MAESTRO dataset, achieving a frame-level F1 score of 0.89 and a note-level F1 of 0.83. The system is optimized for real-time performance on consumer hardware and provides an accessible interface for musicians and educators.
Listen to the result and edit transcriptions within the app. Support: Works for solo piano or with other instruments. Typical Mod/Turbo Features Remove Ads: Eliminates advertisements in the app. piano2notes mod
