Name
Abstract | ||
|---|---|---|
Most commercialized speech recognition systems that have a large capacity and high recognition rates are a type of speaker dependent isolated word recognition systems. In order to extend the scope of recognition, it is necessary to increase the number of words that are to be searched. However, it shows a problem that exhibits a decrease in the system performance according to the increase in the number of words. This paper defines the context information that affects speech recognition in a ubiquitous environment to solve such a problem and designs a new speech recognition system that demonstrates better performances than the existing system by establishing a word model domain of a speech recognition system. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-75664-4_21 | SEUS |
Keywords | Field | DocType |
existing system,speech recognition,speaker dependent isolated word,system performance,word model domain,recognition system,speech recognition system,new speech recognition system,commercialized speech recognition system,ubiquitous environment,high recognition rate,word recognition | Speech analytics,Intelligent character recognition,Computer science,Audio mining,Voice activity detection,Word error rate,Speech recognition,Speaker recognition,Natural language processing,Artificial intelligence,Intelligent word recognition,Acoustic model | Conference |
Volume | ISSN | ISBN |
4761 | 0302-9743 | 3-540-75663-9 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jong-Hun Kim | 1 | 262 | 20.58 |
| Un-Gu Kang | 2 | 34 | 5.48 |
| Kee-Wook Rim | 3 | 154 | 24.20 |
| Jung-Hyun Lee | 4 | 188 | 23.59 |