Fast Partial Tracking of Audio with Real-Time Capability through Linear Programming

Julian Neri; Philippe Depalle
DAFx-2018 - Aveiro
This paper proposes a new partial tracking method, based on linear programming, that can run in real-time, is simple to implement, and performs well in difficult tracking situations by considering spurious peaks, crossing partials, and a non-stationary shortterm sinusoidal model. Complex constant parameters of a generalized short-term signal model are explicitly estimated to inform peak matching decisions. Peak matching is formulated as a variation of the linear assignment problem. Combinatorially optimal peak-to-peak assignments are found in polynomial time using the Hungarian algorithm. Results show that the proposed method creates high-quality representations of monophonic and polyphonic sounds.