Formant Tracking Using Quasi-Closed Phase Forward-Backward Linear Prediction Analysis and Deep Neural Networks. (arXiv:2201.01525v1 [eess.AS])

Formant tracking is investigated in this study by using trackers based on
dynamic programming (DP) and deep neural nets (DNNs). Using the DP approach,
six formant estimation methods were first compared. The six methods include
linear prediction (LP) algorithms, weighted LP algorithms and the recently
developed quasi-closed phase forward-backward (QCP-FB) method. QCP-FB gave the
best performance in the comparison. Therefore, a novel formant tracking
approach, which combines benefits of deep learning and signal processing based
on QCP-FB, was proposed. In …

analysis arxiv formant networks neural networks prediction tracking