Name
Title | ||
|---|---|---|
The Segmental Bayesian Information Criterion and Its Applications to Speaker Diarization |
Abstract | ||
|---|---|---|
This paper discusses the use of the BIC with respect to speaker diarization, i.e., the problem of assigning the observation vectors of an audio file to a set of speakers of unknown cardinality. Our primary goals are to examine the two dominant approaches of the BIC, namely the global and the local and combine the strengths of the two variants into one intuitive criterion, the segmental-BIC. We then consider the asymptotic behavior of the segmental-BIC, when dealing with models that are highly misspecified, as the ones commonly used in the speaker diarization task. Our main result is a modified version of the BIC, which significantly outperforms the current variants over the entire range of operating points, and achieves performance close to those of highly computationally demanding algorithms. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/JSTSP.2010.2048656 | Selected Topics in Signal Processing, IEEE Journal of |
Keywords | Field | DocType |
speaker recognition,BIC,asymptotic behavior,computationally demanding algorithms,segmental Bayesian information criterion,speaker diarization,Bayesian information criterion (BIC),cluster analysis,clustering,speaker diarization (SD) | Bayesian information criterion,The intuitive criterion",Computer science,Cardinality,Speech recognition,Speaker recognition,Speaker diarisation,Artificial intelligence,Cluster analysis,Hidden Markov model,Machine learning,Bayesian probability | Journal |
Volume | Issue | ISSN |
4 | 5 | 1932-4553 |
Citations | PageRank | References |
5 | 0.58 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stafylakis, T. | 1 | 5 | 0.58 |
| Vassilis Katsouros | 2 | 6 | 1.29 |
| Carayannis, G. | 3 | 5 | 0.58 |