Self-organizing-maps with Bic for Speaker Clustering Self-organizing-maps with Bic for Speaker Clustering Itshak Lapidot

@inproceedings{Lapidot2002SelforganizingmapsWB,
  title={Self-organizing-maps with Bic for Speaker Clustering Self-organizing-maps with Bic for Speaker Clustering Itshak Lapidot},
  author={I. Lapidot},
  year={2002}
}
A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a SelfOrganizing-Map (SOM). For estimation of the number of clusters the Bayesian Information Criterion (BIC) is applied. This approach was tested on the NIST 1996 HUB-4 evaluation test in terms of speaker and cluster purities. Results indicate that the combined SOM-BIC approach can lead to better clustering… CONTINUE READING

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