suwoncjh / Noise-Injection-Based-Acoustic-Feedback-Cancellation

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Noise Injection Based Acoustic Feedback Cancellation

Overview

This GitHub repository provides for Noise Injection Based Acoustic Feedback Cancellation.

Abstract: We propose a low latency smartphone-based application that demonstrates the real-time operation to cancel the negative effects of acoustic feedback arising from the coupling between the speaker and the microphone of the smartphone or similar device utilizing the robust Noise Injection (NI) method. We make use of multiple noise injections of short duration to estimate the filter coefficients of an appropriate order between the speaker and the microphone, in order to perform the feedback cancellation effectively in real-time. Our motive behind the development of this application is to perform an effective acoustic feedback cancellation irrespective of the position of speaker and the microphone on the platform under consideration. With the proposed application, we can estimate the transfer function between speaker and microphone in the changing room acoustics making the feedback cancellation very effective. A real-time implementation on an Android-based smartphone is presented in this paper.

You can find the paper for this GitHub repository: https://asa.scitation.org/doi/abs/10.1121/2.0000836

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Requirements

  • Matlab 2016a or newer
  • Visual Studio

License and Citation

The codes are licensed under MIT license.

For any utilization of the code content of this repository, one of the following books needs to get cited by the user:

  • Mishra, Parth, Serkan Tokgoz, and Issa MS Panahi. "Robust real-time implementation of adaptive feedback cancellation using noise injection algorithm on smartphone." In Proceedings of Meetings on Acoustics 175ASA, vol. 33, no. 1, p. 055003. Acoustical Society of America, 2018.

Disclaimer

This work was supported in part by the National Institute of the Deafness and Other Communication Disorders (NIDCD) of the National

Institutes of Health (NIH) under Award 1R01DC015430. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH

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