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.
Cite as: Stone, S., Steiner, P., Birkholz, P. (2017) A Time-Warping Pitch Tracking Algorithm Considering Fast f0 Changes. Proc. Interspeech 2017, 419-423, doi: 10.21437/Interspeech.2017-382
@inproceedings{stone17_interspeech,
author={Simon Stone and Peter Steiner and Peter Birkholz},
title={{A Time-Warping Pitch Tracking Algorithm Considering Fast f0 Changes}},
year=2017,
booktitle={Proc. Interspeech 2017},
pages={419--423},
doi={10.21437/Interspeech.2017-382}
}