# Listening to Sounds of Silence for Speech Denoising

## Supplementary Material

## Overview

This off-line webpage organizes our denoising audio results. We first show the comparison results on `AudioSet` dataset, `DEMAND` dataset and real-world audio recordings. When demonstrating with real-world recordings, we also include scenarios in which audiovisual denoising would fail because of the lack of frontal faces in video footage as well as scenarios in which multiple persons speak. Both are common scenarios in daily life. We then present examples of our denoising results on other languages, which are all resulted from our model trained solely in English. Lastly, we show two clips from the song "The Sound of Silence", as an echo of our title, to further demonstrate our model's ability to reduce non-stationary noise like music.

Please click each item below to see and hear individual audio results.

## Synthetic data: AVSPEECH + Audioset

Here we show denoising results on synthetic input signals. The input signals are generated using audio clips in `AVSPEECH` as foreground speech and in `AudioSet` as background noise. Under seven different input SNRs (from -10dB to 10dB), we compare the denosing results of our model with other methods.

Please note that here the `Ours-GTSI` method uses ground-truth silent interval labels. It is by no means a practical approach. But rather, it is meant to to show the best possible (upper-bound) denoising quality when the silent intervals is perfectly predicted.

- SNR (dB): 10 ｜ Speaker: Nadia Lopez

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 7 ｜ Speaker: Anand Varma

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 3 ｜ Speaker: George Monbiot

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 0 ｜ Speaker: Jennifer Senior

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -3 ｜ Speaker: Nancy Lublin

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -7 ｜ Speaker: Shivani Siroya

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -10 ｜ Speaker: Nathalie Cabrol

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

## Synthetic data: AVSPEECH + DEMAND

Here we provide comparison results similar to the previous section. Instead of using `AudioSet` data as background noise, here we use `DEMAND`, another dataset used in previous denoising works, as the source of background noise. All other setups are the same as the previous section.

- SNR (dB): 10 ｜ Speaker: Aomawa Shields

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 7 ｜ Speaker: Nathalie Cabrol

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 3 ｜ Speaker: Leah Buechley

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): 0 ｜ Speaker: Abe Davis

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -3 ｜ Speaker: Del Harvey

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -7 ｜ Speaker: Manuel Lima

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- SNR (dB): -10 ｜ Speaker: Oded Shoseyov

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Clean Sample |
  Ours-GTSI |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

## Real world data

Here we provide denoising results on real-world recordings, in comparison to other methods. These examples are recorded in video with a single person from front-face view. Only the (mono-channel) audio signals in the recordings are provided to the denoising methods, except `VSE`, which requires audiovisual input (i.e., video footage is also provided as input).

- Speaker: Henrique Maia

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- Speaker: Henrique Maia

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- Speaker: Henrique Maia

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- Speaker: Dana Newman

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

- Speaker: Veronica Montano

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |
  VSE |

## Real world data: Audiovisual failed

Here we provide additional comparison results on examples from real world. `VSE` (the audiovisual method) results are excluded since it cannot successful extract mouth information from these examples.

- Speaker: Female Interviewee

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Female Interviewee

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Female Interviewee

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Mickeyworkstv

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Yusuke Furugen

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Hera Jiwon

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Sliceofmatt

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Speaker: Veronica Montano

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

## Real world data: multi-person

Here we provide additional comparison results on examples from real world where there are more than one person talking. The denoising result is supposed to keep voices from every person.

- Multiple speakers: Richard Hammond & wife

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Multiple speakers: Richard Hammond & wife

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Multiple speakers: Richard Hammond & wife

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

- Multiple speakers: A street interview

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Ours |
  Spectral Gating |
  Adobe Audition |
  DFL |
  SEGAN |
  Baseline-thres |

## Other languages

Here we provide our denoising results on audio examples of other languages. Our silent interval detection results are also provided.

- Chinese ｜ Speaker: Mickeyworkstv

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- Japanese ｜ Speaker: Yusuke Furugen

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- Korean ｜ Speaker: Hera Jiwon

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- German ｜ Speaker: Dana Newman

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- French ｜ Speaker: Sliceofmatt

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- Spanish ｜ Speaker: Veronica Montano

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

- Spanish ｜ Speaker: Veronica Montano

  Results | Audio waveform
  --- | ---
  Noisy Sample |
  Denoised Result |
  Silent Intervals |

## "The Sound of Silence"

Lastly, listen to "The Sound of Silence" by our method that listens to the sounds of silence!

- Excerpt 1 ｜ Singer: Simon & Garfunkel

  Results | Audio waveform
  --- | ---
  Song Excerpt |
  Denoised Result |
  Silent Intervals |

- Excerpt 2 ｜ Singer: Simon & Garfunkel

  Results | Audio waveform
  --- | ---
  Song Excerpt |
  Denoised Result |
  Silent Intervals |