Name
Abstract | ||
|---|---|---|
A standard recipe for spoken language recognition is to apply a Gaussian back-end to i-vectors. This ignores the uncertainty in the i-vector extraction, which could be important especially for short utterances. A recent paper by Cumani, Plchot and Fer proposes a solution to propagate that uncertainty into the backend. We propose an alternative method of propagating the uncertainty. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Machine Learning | Gaussian,Recipe,Artificial intelligence,Natural language processing,Mathematics,Machine learning,Spoken language |
DocType | Volume | Citations |
Journal | abs/1710.00085 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Niko Brümmer | 1 | 595 | 44.01 |
| Albert Swart | 2 | 22 | 3.21 |