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I wonder how these engines compare to cloud services described in [1]. [1]: https://blog.rebased.pl/2016/12/08/speech-recognition-1.html https://blog.rebased.p
by nathell 8y ago
I wonder how these engines compare to cloud services described in [1].
[1]: https://blog.rebased.pl/2016/12/08/speech-recognition-1.html https://blog.rebased.pl/2016/12/08/speech-recognition-1.html
- tootie 8y agoThe cloud options almost certainly have better accuracy and use less memory but it's at the cost of latency, network dependency and usually price.
- glup 8y agoCommercial APIs from leading companies generally achieve better performance, but besides obvious price and network latency, they are complete black boxes so you can't diagnose and fix problems.
- kenarsa 8y agoGreat question. I believe that someone has already performed this measurement on a variety of could APIs (Google, Amazon. MS. etc.). I remember seeing it on GitHub while ago. I can't find it right now with a simple Google search. But I will spend more time later in the evening and comment here when I have it. The comments are absolutely correct. Could services (can) do better simply because they have access to more compute resources and also data (what is sent to them can be/is used for training later). There are situations where on-device is preferred due to privacy reasons, latency, cost, or lack of internet connection.