Name
Title | ||
|---|---|---|
Use of center of gravity with the common vector approach in isolated word recognition |
Abstract | ||
|---|---|---|
In this paper, the subspace based classifier, common vector approach (CVA), with the center of gravity (COG) method is used for isolated word recognition. Since the CVA classifier is sensitive to shifts through the time axis, endpoint detection becomes extremely important for the recognition of isolated words. The COG method eliminates the need for endpoint detection. The effects of the COG method and a classical endpoint detection algorithm on the recognition rates of isolated words are investigated. The experimental results show that the COG method yields slightly higher recognition rates than the endpoint detection method in the TI-digit database when CVA is used. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.eswa.2010.09.026 | Expert Syst. Appl. |
Keywords | Field | DocType |
higher recognition rate,speech recognition,classical endpoint detection algorithm,cva classifier,isolated word recognition,cog method yield,endpoint detection method,isolated word,endpoint detection,recognition rate,common vector approach,center of gravity,cog method,word recognition | Pattern recognition,Subspace topology,Computer science,Word recognition,Speech recognition,Artificial intelligence,Cog,Classifier (linguistics),Center of gravity | Journal |
Volume | Issue | ISSN |
38 | 4 | Expert Systems With Applications |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Bilginer Gülmezoğlu | 1 | 160 | 12.15 |
| Rifat Edizkan | 2 | 93 | 6.97 |
| Semih Ergin | 3 | 26 | 4.00 |
| Atalay Barkana | 4 | 374 | 16.23 |