The application of long-term analysis of the zero-crossing of a speech signal in automatic speaker identification

This paper investigates the possibility of using long-term analysis of the zero-crossings of a speech signal for speaker identification. The applied method of identification is based on an analysis of the signal in measuring windows of a duration which should ensure the stationarity of the statical distributions of the time intervals between successive zero-crossings, in 16 pre-set time channels.
An objective method of defining the minimum length of the measuring window for a selected set of parameters is presented. It is based on the static-narity test and the orgodic theorem for stochastic processes, as is the transfor¬mation of the speech signal mentioned above.. An experiment in speaker identi-fication for 10 speakers with 10 repetitions for each speaker has been performed. The results obtained, in well exceeding 90 % correct identification for 30- and 40 second samples of the speech signal, have confirmed the practicality of the met¬hod of zero-crossing analysis for speaker identification.