The use of harmonic features in speaker recognition

In this paper the harmonic features based on the harmonic decomposition of the Hildebrand-Prony line spectrum are introduced. A Hildebrand-Prony method of spectral analysis was applied because of its high resolution and accuracy. Comparative tests with the linear prediction (LP) and LP-cepstral features were made with 50 speakers from the Slovene database SNABI (isolated words corpus) and 50 speakers of the German database BAS Siemens 100 (utterances of sentences). With both databases the advantages of the harmonic features were noticed especially for the speaker identification while for speaker verification the harmonic features have performed better on the SNABI database and as good as the LP cepstral features on the BAS Siemens 100 database.