Name
Abstract | ||
|---|---|---|
BSTRACTWe present ClearBuds, the first end-to-end hardware and software system that utilizes a neural network to enhance speech streamed from two wireless earbuds. Real-time speech enhancement for wireless earbuds requires high-quality sound separation and background cancellation, operating in real-time and on a mobile phone. Clear-Buds bridges state-of-the-art deep learning for blind audio source separation and in-ear mobile systems by making two key technical contributions: 1) a new wireless earbud design capable of operating as a synchronized, binaural microphone array, and 2) a lightweight dual-channel speech enhancement neural network that runs on a mobile device. Our demo will allow MobiSys attendees wear our earbuds, and experience noise suppression as they talk in a noisy environment. Companion video can be accessed using the link below: |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3498361.3538654 | Mobile Systems, Applications, and Services |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ishan Chatterjee | 1 | 0 | 0.68 |
| Maruchi Kim | 2 | 0 | 1.01 |
| Vivek Jayaram | 3 | 4 | 2.07 |
| Shyamnath Gollakota | 4 | 2788 | 150.48 |
| Ira Kemelmacher-Shlizerman | 5 | 710 | 28.03 |
| Shwetak N. Patel | 6 | 2967 | 211.74 |
| Steven M. Seitz | 7 | 8729 | 495.13 |