Name
Title | ||
|---|---|---|
Interlayer Selective Attention Network for Robust Personalized Wake-Up Word Detection. |
Abstract | ||
|---|---|---|
Previous research methods on wake-up word detection (WWD) have been proposed with focus on finding a decent word representation that can well express the characteristics of a word. However, there are various obstacles such as noise and reverberation which make it difficult in real-world environments where WWD works. To tackle this, we propose a novel architecture called interlayer selective attent... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LSP.2019.2959902 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Acoustics,Encoding,Noise measurement,Task analysis,Robustness,Google,Training data | Wake,Architecture,Word representation,Reverberation,Pattern recognition,Selective attention,Speech recognition,Artificial intelligence,Mathematics | Journal |
Volume | ISSN | Citations |
27 | 1070-9908 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyungjun Lim | 1 | 31 | 7.66 |
| Younggwan Kim | 2 | 17 | 6.11 |
| Jahyun Goo | 3 | 0 | 1.35 |
| Hoirin Kim | 4 | 0 | 1.01 |