The Audio Analysis Lab, represented by Liming Shi, presented a paper on Parkinsons at the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, which was held October 15-18 at Mohonk Mountain House, New Paltz, New York. The lab was also part of the organizing team for this edition of the workshop, as Mads Græsbøll Christensen was Technical Program Co-Chair. The paper was:
A Kalman-Based Fundamental Frequency Estimation Algorithm Liming Shi, Jesper Kjær Nielsen and Jesper Rindom Jensen (Aalborg University, Denmark); Max Little (MIT, USA); Mads Græsbøll Christensen (Aalborg University, Denmark)
Fundamental frequency estimation is an important task in speech and audio analysis. Harmonic model-based methods typically have superior estimation accuracy. However, such methods usually assume that the fundamental frequency and amplitudes are stationary over a short time frame. In this paper, we propose a Kalman filter-based fundamental frequency estimation algorithm using the harmonic model, where the fundamental frequency and amplitudes can be truly nonstationary by modeling their time variations as first-order Markov chains. The Kalman observation equation is derived from the harmonic model and formulated as a compact nonlinear matrix form, which is further used to derive an extended Kalman filter. Detailed and continuous fundamental frequency and amplitude estimates for speech, the sustained vowel /a/ and solo musical tones with vibrato are demonstrated.