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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 intra-frame 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.