3 ms·
"Each time you make a Voice Call on Telegram, a neural network learns from your and your device‘s feedback (naturally, it doesn’t have access to the contents of
by wackspurt 10y ago
"Each time you make a Voice Call on Telegram, a neural network learns from your and your device‘s feedback (naturally, it doesn’t have access to the contents of the conversation, it has only technical information such as network speed, ping times, packet loss percentage, etc.). The machine optimizes dozens of parameters based on this input, improving the quality of future calls on the given device and network."
What sort of parameters are adjusted?
- CodeMichael 10y agoSounds like marketing speech for variable bitrate encoding and/or adjusting compression aggressiveness.
- samat 10y agoThose codecs have tons of parameters to tweak (source: private conversation with Pavel Durov)
- moe 10y agoBut what sort of parameters are adjusted? This is HN. A link to an example would be appreciated. Edit: To clarify, I work with audio codecs too, and can't really think of parameters (other than the compression level?) that would make much sense to adjust on the fly. If "AI" is used for more than just a buzzword here, then I imagine the answer must be quite interesting.
- fenwick67 10y agoThey probably adjust the incoming / outgoing buffer sizes (and therefore the audio delay, since it's live) to account for packet loss. They might also prioritize traffic depending on how full your buffers are. I can only assume Youtube and Netflix do similar parameter tweaks to optimize their video delivery based on the connection (totally filling the buffer to a max size all the time would waste bandwidth, but if the client has lots of packet loss they need a larger safety net).
- pbhjpbhj 10y agoRight, looks like we're up to maybe 6 parameters. The claim was dozens which i take to mean at least 24, possibly 36 as the lower bound.
- JshWright 10y ago> variable bitrate encoding I hope not... VBR can easily leak all sorts of information (including the actual content of the conversation)
- drakenot 10y agoWhoa, I had never thought of monitoring VBR as an attack vector for recovering audio. Do you have a link discussing this?
- JshWright 10y agoSure, here are a couple papers on the topic: https://www.cs.jhu.edu/~cwright/oakland08.pdf https://www.cs.jhu.edu/~cwright/oakland08.pdf https://www.cs.jhu.edu/~cwright/voip-vbr.pdf https://www.cs.jhu.edu/~cwright/voip-vbr.pdf It's fundamentally very similar to the sorts of issues you end up with if you compress then encrypt. If the attacker can make some educated guesses about the plaintext prior to the compression, the compression ratio can be a very powerful tool in their arsenal.
- walterbell 10y agoWire implemented CBR for their encrypted calls, upstreamed it to WebRTC and submitted a patch to Signal, https://medium.com/wire-news/call-security-constant-bit-rate-encoding-and-improving-webrtc-a85be6caa43a https://medium.com/wire-news/call-security-constant-bit-rate...
- JshWright 10y agoSilent Phone has used CBR since day 1.
- CodeMichael 10y agoCorrect, last article I recall reading about deciphering VBR from packet size alone was something in the neighborhood of 50% success rate.
- tyingq 10y agoI have the feeling that's there soley for the "AI-Powered" hype train benefit. Versus actually being used as a genuine feedback loop to improve the service. Logs of speed, ping times, packet loss, would likely be more useful in good old, non-AI reports...to identify regional issues, peering opportunities, etc. I don't think you need AI for voip calls that upgrade/degrade quality based on network health.