In this paper, we examine the use of i-vectors both for age regression
as well as for age classification. Although i-vectors have been previously
used for age regression task, we extend this approach by applying fusion
of i-vectors and acoustic features regression to estimate the speaker
age. By our fusion we obtain a relative improvement of 12.6% comparing
to solely i-vector system.
We also use i-vectors
for age classification, which to our knowledge is the first attempt
to do so. Our best results reach unweighted accuracy 62.9%, which is
a relative improvement of 16.7% comparing to the best results obtained
in age classification task at Age Sub-Challenge at Interspeech 2010.