We have already proposed a robust fundamental frequency (F0) estimation based on robust ELS (Extended Least Square) timevarying complex-valued speech analysis for an analytic speech signal. It has been reported that the method performs better for IRS filtered speech corrupted by white Gauss noise or pink noise since speech spectrum can be accurately estimated in low frequencies. However, the evaluation was performed by using only time-invariant speech analysis, in which order of basis expansion was 1. In this paper, the performance of time-varying speech analysis is evaluated using Keele pitch database with respect to degree of voiced stationarity of frame. The evaluation demonstrates that the time-varying ELS-based robust complex analysis performs best for strong stationary voiced frame although it does not perform better for non-stationary voiced frame.
Bibliographic reference. Funaki, Keiichi (2010): "On evaluation of the f0 estimation based on time-varying complex speech analysis", In INTERSPEECH-2010, 637-640.