Longterm Speech Spectra of Nonstationary Autoregressive Models

摘要

Long term time-frequency spectra of words were obtained using autoregressive methods to characterize complete words without segmentation. The resulting spectra and the time dependent coefficients of the AR filter are compared with the short term stationary case. Examples show a better accuracy given by discussed method, in spite of the reduced number of parameters involved in the proposed representation.