Voiced-unvoiced-silence detection using the Itakura LPC distance measure
L. R. Rabiner, M. R. Sambur · 2005
One of the most difficult problems in speech analysis is reliable discrimination among silence, unvoiced speech, and voiced speech which has been transmitted over a telephone line. Although several methods have been proposed for making this 3-level decision, these schemes have met with only modest success. In this paper a novel approach to the voiced-unvoiced-silence detection problem is proposed in which a spectral characterization of each of the 3 classes of signal is obtained during a training session, and an LPC distance metric and an energy distance are nonlinearly combined to make the final discrimination. This algorithm has been tested over conventional switched telephone lines, across a variety of speakers, and has been found to have an error rate of about 5%, with the majority of the errors (about 2/3) occurring at the boundaries between signal classes. The algorithm is currently being used in a speaker independent word recognition system.