Name
Abstract | ||
|---|---|---|
We report investigations into speaker classification of larger quantities of unlabelled speech data using small sets of manually phonemically annotated speech. The Kohonen speech typewriter is a semi-supervised method comprised of self-organising maps (SOMs) that achieves low phoneme error rates. A SOM is a 2D array of cells that learn vector representations of the data based on neighbourhoods. In this paper, we report a method to evaluate pronunciation using multilevel SOMs with /hVd/ single syllable utterances for the study of vowels, for Australian pronunciation. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Computation and Language | Pronunciation,Computer science,Self-organizing map,Speech recognition,Syllable,Natural language processing,Artificial intelligence,Self organising maps |
DocType | Volume | Citations |
Journal | abs/1702.02092 | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tom A. F. Anderson | 1 | 6 | 1.12 |
| David M. W. Powers | 2 | 500 | 67.39 |