In this paper, we prove that the direction of cepstrum vectors strongly depends on vocal tract length and that this dependency is represented as rotation in a cepstrum space. In speech recognition studies, vocal tract length normalization (VTLN) techniques are widely used to cancel ageand gender-difference. In VTLN, a frequency warping is often carried out and it can be modeled as a linear tran...

This paper aims at speaker recognition based upon a novel set of features. Feature extraction is a crucial phase of the speaker recognition process and a proper feature set can influence it dramatically. Many well-known features are not suitable for the speaker recognition as those merge the specifics of the individual voices to make them universal. Therefore, we need features accentuating the ...

Several papers have been devoted to the alternative maximum entropy method (MEM2) which uses a finite-length cepstrum modelling to estimate the spectrum from a given set of autocorrelations. In this paper, a simple technique that avoids the computational burden of MEM2 by using the causal part of the autocorrelation instead of the complete two-sided sequence is presented. Its finite-length ceps...

Robust speaker feature extraction under noise conditions is an important issue for application of a speaker recognition system. It is well known that LPC cepstrum, which expresses the spectral envelope, is e ective for speaker recognition. This implies that the spectral rough structure is e ective for speaker recognition. However, LPC cepstrum is a noise-sensitive feature. On the other hand, sp...