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ClearBuds: Wireless Binaural Earbuds for Learning-based Speech Enhancement

Abstract

We 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. ClearBuds 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. Results show that our wireless earbuds achieve a synchronization error less than 64 us and our network has a runtime of 21.4 ms on an accompanying mobile phone. In-the-wild evaluation with eight users in previously unseen indoor and outdoor multipath scenarios demonstrates that our neural network generalizes to learn both spatial and acoustic cues to perform noise suppression and background speech removal. In a user-study with 37 participants who spent over 15.4 hours rating 1041 audio samples collected in-the-wild, our system achieves improved mean opinion score and background noise suppression.

Setup

  1. Download nRF SDK
  1. Install toolchains
  1. Clone the repo
  • Clone anywhere, and overwrite this repo's SDK/modules/nrfx/drivers/src/nrfx_pdm.c file over the stock version of the file provided by the nRF SDK.
  • Once overwritten, copy over the entire SDK directory into this repository
  1. Build and flash
  • Run 'make flash' in terminal to build and flash

If you have any trouble installing, feel free to reach out, more details for setting up on a mac can be found here: https://aaroneiche.com/2016/06/01/programming-an-nrf52-on-a-mac/

License

This project is under the GNU General Public License v3.0. See the COPYING file for the full license text.

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