Transkun — is a modern open-source model for automatic piano music transcription (Audio-to-MIDI). The official page of the model is here. It is considered one of the best (SOTA — State of the Art) in its class. The model can recognize not only the notes themselves but also their duration, loudness (velocity), and pedal usage. Unlike many older models that analyze music «frame-by-frame» (frame-based), Transkun uses the Neural Semi-CRF (semi-Markov Conditional Random Field) approach. Instead of asking «is a note sounding at this millisecond?», the model treats events as whole intervals (from the start to the end of the note). The latest versions use a Transformer (Non-Hierarchical Transformer) which calculates the probability that a specific time segment is a note. Decoding: The Viterbi algorithm is used to find the most probable sequence of non-overlapping intervals. The model demonstrates excellent results on the MAESTRO dataset (the industry standard).