31–40 of 109 posts
Here's to hoping they make a version for Windows and/or Linux. Mac support is nice, but this seems business-focused (though handy for casual use). Most businesses, especially outside of Silicon Valley, don't use Mac; Windows will likely be a larger market.
2Hz CEO here (we built Krisp). Windows support will come in Dec. We are working hard on it.
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Mobile support is harder since Krisp won't be able to register as a virtual mic/speaker on Android or iOS. At least we haven't found any way around it.
There's an app for Android called SoundAbout, which can reroute audio. Not sure how it works, but maybe something similar is possible for Krisp? https://play.google.com/store/apps/details?id=com.woodslink....
All audio is processed on device, but is the goal to use the public training/learning to tailor a more robust model which they can sell commercially/integrate into apps/phones/etc?
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Make sure you check back in with the results!
As requested: This call typically has decent audio quality, and as it's a stand-up / status call people tend to speak one at a time. No-one today had much in the way of background noise, so I'm not sure there was a lot of opportunity for the app to show off. That said, I switched the Krisp speaker mode on and off repeatedly while each person who was talking. 1. When just one person was talking Krisp didn't seem to ev…
Re #2, one thing we noticed is that Conferencing apps themselves will distort the voice when multiple voices are overlapping. Especially when there is also noise. There is not much Krisp can do here since the stream it receives is already distorted. Unfortunately for krisp speaker we don't control the audio stream. Imagine how many times the stream gets signal processed before krisp speaker gets it (noise cancellation in the headset, noise cancellation in RTC, codec, etc).
Re Krisp microphone, the DNN model used here is more effective since what Krisp receives is "less processed/distorted stream".
Please stay tuned, our release cycle is around 2 weeks. More quality and UX features are under way.
How do they make money? All audio is processed on device, but is the goal to use the public training/learning to tailor a more robust model which they can sell commercially/integrate into apps/phones/etc?
How do they make money? All audio is processed on device, but is the goal to use the public training/learning to tailor a more robust model which they can sell commercially/integrate into apps/phones/etc?