  At present Automatic Speaker Recognition system is a very important issue due
to its diverse applications. Hence, it becomes absolutely necessary to obtain
models that take into consideration the speaking style of a person, vocal tract
information, timbral qualities of his voice and other congenital information
regarding his voice. The study of Bengali speech recognition and speaker
identification is scarce in the literature. Hence the need arises for involving
Bengali subjects in modelling our speaker identification engine. In this work,
we have extracted some acoustic features of speech using non linear
multifractal analysis. The Multifractal Detrended Fluctuation Analysis reveals
essentially the complexity associated with the speech signals taken. The source
characteristics have been quantified with the help of different techniques like
Correlation Matrix, skewness of MFDFA spectrum etc. The Results obtained from
this study gives a good recognition rate for Bengali Speakers.
