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Efficient combination of parametric spaces , models and metrics for speaker diarization 1 A Maximum Entropy Approach
| Content Provider | Semantic Scholar |
|---|---|
| Author | Stafylakis, Themos Katsouros, Vassilis Carayannis, George B. |
| Copyright Year | 2007 |
| Abstract | In this paper we present a method of combining several acoustic parametric spaces, statistical models and distance metrics in speaker diarization task. Focusing our interest on the post-segmentation part of the problem, we adopt an incremental feature selection and fusion algorithm based on the Maximum Entropy Principle and Iterative Scaling Algorithm that combines several statistical distance measures on speech–chunk pairs. By this approach, we place the merging–of–chunks clustering process into a probabilistic framework. We also propose a decomposition of the input space according to gender, recording conditions and chunk lengths. The algorithm produced highly competitive results compared to GMM-UBM state-ofthe-art methods. Keywords— Speaker Diarization; Maximum Entropy; Fusion Topic area— Singleand Multimedia Indexing |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ilsp.gr/homepages/docs/Efficientcombination2007.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
