A Time-Warping Pitch Tracking Algorithm Considering Fast f0 Changes

Accurately tracking the fundamental frequency (f0) or pitch in speech data is of great interest in numerous contexts. All currently available pitch tracking algorithms perform a short-term analysis of a speech signal to extract the f0 under the assumption that the pitch does not change within a single analysis frame, a simplification that introduces errors when the f0 changes rather quickly over time. This paper proposes a new algorithm that warps the time axis of an analysis frame to counteract intraframe f0 changes and thus to improve the total tracking results. The algorithm was evaluated on a set of 4718 sentences from 20 speakers (10 male, 10 female) and with added white and babble noise. It was comparative in performance to the state-of-the-art algorithms RAPT and PRAAT to Pitch (ac) under clean conditions and outperformed both of them under noisy conditions.