61–70 of 109 posts
As an amateur radio operator, I struggle very often with noise-related issues. Nice tech. I'm used to see digital processing applying in this field, but never thought about applying machine learning. Feeling curious about learning about the technology some day, because, for me, based on the solutions I currently know, this seems, indeed, magic.
https://devblogs.nvidia.com/nvidia-real-time-noise-suppressi...
Is there a way to run an existing audio file through this to clean it up? For example, if I have a video of a presentation with lots of background noise like chairs creaking, people coughing, etc.?
Here is demo link that you can use for that purpose. https://demo.2hz.ai/ We are also building web and iOS apps to cancel the noise in the files.
My first internship was at a company that was doing this over a decade ago, but before machine learning had proliferated to adjacent fields. It's easy to separate out stationary signals like ambient noise, which are easily isolated in the frequency domain. But it's a totally different thing to remove something like a baby's cry, shuffling of papers, or other sharp transients. Blindly separating without a large corpus…
I'd be a little worried about the feature that fills in missing voice chunks. It sounds ripe for accidentally replacing one lost word with a completely different word that could also make sense in context. Almost like the issue where Xerox copiers would sometimes replace one character with another. Hopefully the filling in of missing chunks is done in a way that doesn't allow it to fill in whole words, but rather jus…
For awhile, it seemed like the autocorrection in iOS was deliberately trying to break up me and my then-girlfriend. It even seemed to have a penchant for doing an unfortunate autocorrect just a sliver of a second before my finger hit send on a txt. I finally turned the feature off.
Is there a way to run an existing audio file through this to clean it up? For example, if I have a video of a presentation with lots of background noise like chairs creaking, people coughing, etc.?
Here is demo link that you can use for that purpose. https://demo.2hz.ai/ We are also building web and iOS apps to cancel the noise in the files.
I still plan to play with the app for voice chat, though.
My first internship was at a company that was doing this over a decade ago, but before machine learning had proliferated to adjacent fields. It's easy to separate out stationary signals like ambient noise, which are easily isolated in the frequency domain. But it's a totally different thing to remove something like a baby's cry, shuffling of papers, or other sharp transients. Blindly separating without a large corpus…
There is a new paper out from Google research that specifically addresses the use case with screaming children in the background - very exciting! https://www.youtube.com/watch?v=zL6ltnSKf9k
This was a sensitive use case for the team since I (CEO/krisp) had a baby 3 days ago and really needed Krisp to do my calls :)
Earlier quoted context omitted.
My suspicion is that the founders/engineers will be acqui-hired for a not-insignificant sum by one of the existing big players in the teleconference space (Zoom, Google, Cisco, etc.).
Further, this is probably their goal. In fact, I wouldn't be surprised if Apple bought something like this as system-wide background noise canceling would be a fantastic OS feature.