101–110 of 157 posts
Earlier quoted context omitted.
Citation?
There is this new type of trolling where someone just puts in bare minimal counterarguments and asks for citations knowing full well it's labour intensive to do so. If your not trolling.. your not doing a good job of avoiding these comparisons. The onus should be on you here to provide citations first that dissprove the person your replying to.
Earlier quoted context omitted.
Citation?
There is this new type of trolling where someone just puts in bare minimal counterarguments and asks for citations knowing full well it's labour intensive to do so. If your not trolling.. your not doing a good job of avoiding these comparisons. The onus should be on you here to provide citations first that dissprove the person your replying to.
Earlier quoted context omitted.
Unless you very recently (meaning today) accepted a download of a new language pack for English, it's likely just the old model, which is perfectly functional, while not being as accurate as the online version.
More specifically: Gboard > Voice Typing > Faster voice typing It says its an 85MB download for US-English
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Ok, so what are the advantages of RNN over CNN based models for speech to text, with respect to any one of those factors you mentioned?
Well for example, some comparisons to the CNN paper you pointed to: - No comparison is given of number of model parameters. If optimizing strictly for model size, RNNs tend to be nice and compact. - The computational advantage of the CNN at training time is throughput. The advantage of RNN at decoding time is streaming latency. Running the CNN frame by frame as they are received removes the ability to run frames in p…
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Interesting that they're using RNN transducer. I thought everyone's moved to CNN lately.
Sorry to go on a tangent, but this is the first time I've heard the word "transducer" outside of a conversation about clojure. Is it the same concept?
const mapTrans = fn => function* (x) {
yield fn(x);
};
const filterTrans = predicate => function* (x) {
if (predicate(x)) {
yield x;
}
};
const dupeTrans = n => function* (x) {
for (let i = 0; i An RNN transducer is fundamentally three functions:
One takes a list of recent As to some C1.
Another takes a list of recent Bs to some C2.
A final one takes a C1 and C2 to a B.
Rather than mapping over each input independently the RNN-T is allowed to learn something about the relationship of recent outputs to the next output, and the relationship of nearby inputs. Clojure transducers thus have an order insensitivity that RNN transducers are allowed to be sensitive to.
Finally google has caught up to 1997: https://en.wikipedia.org/wiki/Dragon_NaturallySpeaking Sure it might work better now, but that's expected when computers are much more powerful than a pentium 100 with 32MB of RAM. Uploading voice to google servers for processing was always just a data grab.
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The offline aspect is hardly the main draw here though. As mentioned earlier in the article, the latency reduction is huge. Another aspect they didn't really cover is privacy implications. Lastly, you may not be offline, but dodgy connections can also be a pain if you need a stable stream of packets going back and forth.
I refuse to put an amazon/apple/google surveillance device in my home, so I am very interested in a DIY digital assistant device. I'm aware of a few options but it seems like offline voice recognition is always a little sub-par. I am really looking forward to the day when an offline, open source digital assistant can compare in quality to a proprietary/cloud device.
This was before the cloudamagig, so I wonder it ran on.
Edit: found the link https://www.techrepublic.com/article/solutionbase-using-spee...
Earlier quoted context omitted.
Citation?
There is this new type of trolling where someone just puts in bare minimal counterarguments and asks for citations knowing full well it's labour intensive to do so. If your not trolling.. your not doing a good job of avoiding these comparisons. The onus should be on you here to provide citations first that dissprove the person your replying to.
Call me cynical but I cannot picture Google not tapping into everything you run through their voice recognition software, even if it does work offline. Doesn't mean it won't phone home later.
For what? They only really make their money on ads for things you're actively searching for. Everything else they have in ads works rather poorly in the text world. Trying to interpret interests out of task-driven voice commands is way beyond their capabilities. But, enough of that. I'm holding out until decent voice dictation is standard everywhere and a well understood engineering problem with good open source impl…
I guess another assumption could be "they have more than enough voice data to train any future network improvements." While I feel they have a lot of voice data, I am skeptical to say that they wouldn't view more data as useful, or at least potentially useful.
I cannot think of a compelling reason for why they would stop collecting data all of a sudden. Can you? (Serious question, I don't mean to sound snarky)