Name
Abstract | ||
|---|---|---|
This paper presents a novel algorithm for precise spotting of plosives. The algorithm is based on a pattern matching tech- nique implemented with margin classifiers, such as support vec- tor machines (SVM). A special hierarchical treatment to over- come the problem of fricative and false silence detection is pre- sented. It uses the loss-based multi-class decisions. Further- more, a method for smoothing the overall decisions by sequen- tial linear programming is described. The proposed algorithm was tested on the TIMIT corpus, which produced a very high spotting accuracy. The algorithm presented here is applied to plosives detection, but can easily be adapted to any class of phonemes. |
Year | Venue | Keywords |
|---|---|---|
2001 | INTERSPEECH | pattern matching,linear program |
Field | DocType | Citations |
TIMIT,Pattern recognition,Computer science,Support vector machine,Speech recognition,Smoothing,Linear programming,Artificial intelligence,Spotting,Pattern matching | Conference | 5 |
PageRank | References | Authors |
0.58 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joseph Keshet | 1 | 925 | 69.84 |
| Dan Chazan | 2 | 71 | 10.85 |
| Ben-Zion Bobrovsky | 3 | 25 | 7.55 |