Name
Abstract | ||
|---|---|---|
Machine Learning (ML) techniques are applied to solve automation tasks in more and more scenarios of our daily life. For instance, Keyword Spotting applications are of interest for Internet-of-things devices in a smart home or for human-machine interaction. Different ML techniques, such as Neural Networks including Long-Short Term Memories, recently achieve reasonable accuracy above 95 % [1]. Therefore, we propose an accelerator for the Keyword spotter as a specialized coprocessor in order to retain the flexibility to fit different network structures, while the energy efficiency is increased. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/NorCAS57515.2022.9934553 | 2022 IEEE Nordic Circuits and Systems Conference (NorCAS) |
Keywords | DocType | ISBN |
ARC-coprocessor,LSTM based audio applications,automation tasks,keyword spotting,Internet-of-Things devices,smart home,human-machine interaction,neural networks,long-short term memories,network structures,machine learning,energy efficiency | Conference | 979-8-3503-4551-3 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastian Birke | 1 | 0 | 0.34 |
| Bjoern Hartmann | 2 | 0 | 0.34 |
| Dominik Auras | 3 | 0 | 0.34 |
| Markus Wloka | 4 | 0 | 0.34 |
| Gerd Ascheid | 5 | 1205 | 144.76 |
| Rainer Leupers | 6 | 1389 | 136.48 |