Speaker age classification and regression using i-vectors

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.