4 ms·

Much much better, I really recommend DeepFilterNet, it's the most well-rounded open-source AI noise suppression tool out there. Big caveat, it won't help ASR mo

Much much better, I really recommend DeepFilterNet, it's the most well-rounded open-source AI noise suppression tool out there. Big caveat, it won't help ASR model, e.g., Whisper. Source: I work in this research area.

SergeAx 3y ago
Do you know a framework to quantitatively compare noise suppression quality produced by different algos? Or maybe there is a industry-standard test suite?
- thatsadude 3y ago
  The golden standard is ITU-T P.808 subject test https://github.com/microsoft/P.808 https://github.com/microsoft/P.808 Of course, running a subjective test is expensive, and hence, there are objective scores such as DNSMOS and UTMOS which use neural networks to predict P808 values.
  - deleted 3y ago
    [deleted]
  - SergeAx 3y ago
    Thank you so much!
MacsHeadroom 3y ago
> Big caveat, it won't help ASR model, e.g., Whisper. Why not?
- thatsadude 3y ago
  Few reasons: 1. Speech distortion is extremely detrimental to ASR models while human listeners may not be able to notice. Noise reduction models such as RNNNoise and DeepFilterNet try to reduce "perceptible" noises. And doing that will create imperceptible distortion which ASR models does not like at all. 2. Many noise reduction models apply on raw spectrograms or ERB band such as RNNNoise and DeepFilterNet (equivalent rectangular bands). On the other hands, ASR models mostly run on melspectrograms. This mismatch tends to create problem. I have seen many papers from Google claimed that reducing noise in melspectrogram often helps their keyword spotting.
peepwaah 3y ago
Hey thatsadude, thanks for your input! I'm also working in this research area and it would be great to connect with you on LinkedIn. Here's my proxy LinkedIn Profile - https://bit.ly/3ChXFcm https://bit.ly/3ChXFcm. If you're interested, could you send me a connection request? Looking forward to connecting and discussing more in the future!

SergeAx 3y ago

Do you know a framework to quantitatively compare noise suppression quality produced by different algos? Or maybe there is a industry-standard test suite?

thatsadude 3y ago
The golden standard is ITU-T P.808 subject test https://github.com/microsoft/P.808 https://github.com/microsoft/P.808 Of course, running a subjective test is expensive, and hence, there are objective scores such as DNSMOS and UTMOS which use neural networks to predict P808 values.
- deleted 3y ago
  [deleted]
- SergeAx 3y ago
  Thank you so much!

MacsHeadroom 3y ago

> Big caveat, it won't help ASR model, e.g., Whisper. Why not?

thatsadude 3y ago
Few reasons: 1. Speech distortion is extremely detrimental to ASR models while human listeners may not be able to notice. Noise reduction models such as RNNNoise and DeepFilterNet try to reduce "perceptible" noises. And doing that will create imperceptible distortion which ASR models does not like at all. 2. Many noise reduction models apply on raw spectrograms or ERB band such as RNNNoise and DeepFilterNet (equivalent rectangular bands). On the other hands, ASR models mostly run on melspectrograms. This mismatch tends to create problem. I have seen many papers from Google claimed that reducing noise in melspectrogram often helps their keyword spotting.

peepwaah 3y ago

Hey thatsadude, thanks for your input! I'm also working in this research area and it would be great to connect with you on LinkedIn. Here's my proxy LinkedIn Profile - https://bit.ly/3ChXFcm https://bit.ly/3ChXFcm. If you're interested, could you send me a connection request? Looking forward to connecting and discussing more in the future!