Intra-session and inter-session variability in the Multi-session Audio Research Project (MARP) corpus are contrasted in two experiments that exploit the long-term nature of the corpus. In the first experiment, Gaussian Mixture Models (GMMs) model 30-second session chunks, clustering chunks using the Kullback-Leibler (KL) divergence. Cross-session relationships are found to dominate the clusters. Secondly, session detection with 3 variations in training subsets is performed. Results showed that small changes in long-term characteristics are observed throughout the sessions. These results enhance understanding of the relationship between long-term and short-term variability in speech and will find application in speaker and speech recognition systems.
Bibliographic reference. Godin, Keith W. / Hansen, John H. L. (2010): "Session variability contrasts in the MARP corpus", In INTERSPEECH-2010, 298-301.