Reducing F0 Frame Error of F0 tracking algorithms under noisy conditions with an unvoiced/voiced classification frontend

@article{Chu2009ReducingFF,
  title={Reducing F0 Frame Error of F0 tracking algorithms under noisy conditions with an unvoiced/voiced classification frontend},
  author={Wei Chu and Abeer Alwan},
  journal={2009 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2009},
  pages={3969-3972}
}
In this paper, we propose an F0 Frame Error (FFE) metric which combines Gross Pitch Error (GPE) and Voicing Decision Error (VDE) to objectively evaluate the performance of fundamental frequency (F0) tracking methods. A GPE-VDE curve is then developed to show the trade-off between GPE and VDE. In addition, we introduce a model-based Unvoiced/Voiced (U/V) classification frontend which can be used by any F0 tracking algorithm. In the U/V classification, we train speaker independent U/V models, and… CONTINUE READING
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