Hierarchical speaker clustering methods for the NIST i-vector Challenge

@inproceedings{Khoury2014HierarchicalSC,
  title={Hierarchical speaker clustering methods for the NIST i-vector Challenge},
  author={Elie Khoury and Laurent El Shafey and Marc Ferras and S{\'e}bastien Marcel},
  year={2014}
}
The process of manually labeling data is very expensive and sometimes infeasible due to privacy and security issues. This paper investigates the use of two algorithms for clustering unlabeled training i-vectors. This aims at improving speaker recognition performance by using state-of-the-art supervised techniques in the context of the NIST i-vector Machine Learning Challenge 2014. The first algorithm is the well-known Ward clustering that aims at optimizing an objective function across all… CONTINUE READING
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