September 22-25, 1997
In this paper a method to decompose a conventional feature space (LPC-cepstrum) into subspaces which carry information about the linguistic and speaker variability is presented. Principal component analysis is used to study the correlation between these sub-spaces. Oriented principal component analysis (OPCA) is then used to estimate a sub-space which is relatively speaker- independent. A method to estimate the dimensionality of the speaker independent sub- space is also presented. Original features can now be projected into the speaker independent sub-space to make them less sensitive to speaker variations. Finally the effectiveness of the proposed method in suppressing the speaker dependence is studied by experiments conducted on two different databases.
Bibliographic reference. Malayath, Narendranath / Hermansky, Hynek / Kain, Alexander (1997): "Towards decomposing the sources of variability in speech", In EUROSPEECH-1997, 497-500.