Name
Abstract | ||
|---|---|---|
Voice activity detection (VAD) classifies incoming signal segments into speech or background noise; its performance is crucial in various speech-related applications. Although speech-signal context is a relevant VAD asset, its usefulness varies in unpredictable noise environments. Therefore, its usage should be adaptively adjustable to the noise type. This letter improves the use of context inform... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LSP.2018.2811740 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Speech,Training,Voice activity detection,Feature extraction,Decoding,Noise measurement,Adaptation models | Background noise,Pattern recognition,Voice activity detection,Attention model,Artificial intelligence,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
25 | 8 | 1070-9908 |
Citations | PageRank | References |
3 | 0.42 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juntae Kim | 1 | 9 | 8.72 |
| Minsoo Hahn | 2 | 223 | 46.63 |