Selection of acoustic features for speaker identification

The aim of this study was to determine a set of acoustic features in the speech signal that are effective for the identification of a speaker. The investigation examined a large number of theoretically attractive features. The analysis technique of linear prediction was incorporated to examine features that were previously ignored because their measurement was either too time consuming or not easily amenable to automatic measurement. A novel probability of error criterion was used to determine the the relative merits of the features. The experimental data base was collected over a year period and afforded the oportunity to investigate the variation over time of the measurements. The measurements that were found to be the most important were the value of the second resonance (around 1000 Hz) in /n/, the value of the third or fourth resonance (1700-2000 Hz) in /m/ the values of the second, third and fourth formant frequencies in vowels, and the average fundamental frequency of the speaker. A speaker identification experiment using only the best five features was performed. The test data consisted of the multisession data of 11 speakers, and the test data was kept independent of the design data. One error was made in the identification of these speakers for 320 separate identification experiments.