Self-Organizing-Maps With BIC For Speaker Clustering
| Type of publication: | Idiap-RR |
| Citation: | lapidot-rr02-60 |
| Number: | Idiap-RR-60-2002 |
| Year: | 2002 |
| Institution: | IDIAP |
| Address: | Martigny, Switzerland |
| Abstract: | 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 Self- Organizing-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 results than the baseline system. |
| Userfields: | ipdinar={2002}, ipdmembership={speech}, language={English}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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