A service framework of humanoid in daily life
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Multiharmonic frequency tracking method using the sigma-point kalman smoother
EURASIP Journal on Advances in Signal Processing
Single-channel speech separation based on long-short frame associated harmonic model
Digital Signal Processing
Robotics and Autonomous Systems
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This paper addresses the joint estimation and detection of time-varying harmonic components in audio signals. We follow a flexible viewpoint, where several frequency/amplitude trajectories are tracked in spectrogram using particle filtering. The core idea is that each harmonic component (composed of a fundamental partial together with several overtone partials) is considered a target. Tracking requires to define a state-space model with state transition and measurement equations. Particle filtering algorithms rely on a so-called sequential importance distribution, and we show that it can be built on previous multipitch estimation algorithms, so as to yield an even more efficient estimation procedure with established convergence properties. Moreover, as our model captures all the harmonic model information, it actually separates the harmonic sources. Simulations on synthetic and real music data show the interest of our approach