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Google’s new voice recognition system works instantly and offline (Pixel only)

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Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#91

Post by pakl »

p1esk wrote: post #74
robbomacrae wrote: post #69

Earlier quoted context omitted.

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.

I'm not trolling. The statement that RNN are somehow more noise-tolerant than CNNs does not make sense to me, and is not based on any literature about noise tolerance in NNs that I'm familiar with. Also, no arguments have been provided as to why this could possibly be the case.

Hi p1esk, RNNs can be more tolerant to noise because they can learn transient or dynamic attractors. If the inputs move an RNN into an attractor, small changes due to noise make little difference to the state.

Recurrence can help with robustness in some other very important ways as well.

Citations for this dates from the 80s and 90s. I don't know the best reference offhand. You could look at some old Hinton stuff if you're a fan. Lots published on this.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#92

Post by joshvm »

adzm wrote: post #39

Does the Pixel have some specific hardware that this uses, or is it simply limited to Pixel to limit the rollout? I am curious if I should get my hopes up to see this on gboard with non-Pixel Android devices.

The Pixel 2+ does have a coprocessor for compute workloads (the Visual Core). However users here have reported this working on a Pixel 1, which doesn't have that chip.

The Verge says it may reach other devices later.

It sounds like it's both better than the old dictation model, and significantly smaller.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#93

Post by vsef »

p1esk wrote: post #62
vsef wrote: post #58

Earlier quoted context omitted.

They're not that I know of. But the paper cited is just showing relative parity or slight improvement on relatively toy examples. The claim that convnets are the clear winner for speech in general/what everyone is doing now is just not true. I work in the field, a more accurate summary would be that there are a number of viable architectures that currently get fairly similar accuracy, but that have other pros/cons wi…

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 parallel and if the CNN is larger, it will run slower, and depending on its receptive fields it may not even stream well at all.

- That particular CNN system uses a strictly external LM that is not jointly trained and has an additional hyper parameter at decoding time to weight the LM that requires additional tuning.

- It is still autoregressive in the beam search, so the LM will still be run many times sequentially adding tokens just like an RNN LM, and is likely to be more expensive. The throughput advantage a conv lm has in scoring whole sentences is totally lost. In fact, there doesn't seem to be anything special about the choice of a conv lm for that paper except that it is fun to make all the parts convolutional.

- CNNs frequently require more total flops, but are high throughput on eg a GPU because they expose so much parallelism. On an embedded CPU this can be a bad tradeoff.

As a side note, there's no reason that CNN architecture, which in the paper is trained with a close relative of CTC and is decoded identically to a RNN CTC AM + external LM, couldn't be trained as an RNN transducer. Despite the name neither the am nor lm have to actually be RNNs.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#94

Post by sgc »

ehsankia wrote: post #59
__jal wrote: post #53

Earlier quoted context omitted.

I doubt it. I generally think of Google the same way I think of the NSA. If they stop doing something invasive, either it didn't work, they found a better way of doing it, or it was transferred to a legally distinct category, and we only hear about it because of PR considerations.

That's a pessimistic way of looking at it. Personally, from my experience, it's the exact opposite: If they're doing something invasive, it's because the data actually powers a feature so valuable that it's generally worth it.

Since I use dictation so much, I hope others don't use it as much, and google uses/prioritizes more of my speech. But I don't use dictation with sensitive data so I don't worry about privacy in this particular instance.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#95

Post by pdog »

pault wrote: post #83
ehsankia wrote: post #57

Earlier quoted context omitted.

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.

> I refuse to put an amazon/apple/google surveillance device in my home...

Do you have a smartphone? Because that's most likely an Apple or Google surveillance device.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#96

Post by jfoster »

melling wrote: post #2

"But it’s sort of funny considering hardly any of Google’s other products work offline. Are you going to dictate into a shared document while you’re offline? Write an email? Ask for a conversion between liters and cups? You’re going to need a connection for that!" While offline, you might write email drafts, your blog, or even a book: https://medium.com/@augustbirch/what-i-learned-writing-an-en... What's missing is t…

Most of their products work offline and sync when a connection is regained. That includes Google Docs and Gmail.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#97

Post by JulianSlzr »

GistNoesis wrote: post #44
p1esk wrote: post #33

Earlier quoted context omitted.

I take it you haven't been following the field lately, have you? It is surprising because convnets just work better for speech recognition ([1] is the latest SOA). I'm guessing gated convolutional LMs are slower than RNN transducers when deployed on mobile. Can someone confirm? [1] https://arxiv.org/abs/1812.06864

There is also the transformer approach (eventually with local attention to bound latency), (like I'm doing in my project (Work in Progress) : https://github.com/GistNoesis/Wisteria/blob/master/SpeechToT... ), though it's in the same line of thought as the convolutional CTC. The RNN-T is a nice idea though, if I understand it correctly it's another approach to the alignment problem. In CTC, you are generating sequence…

We explored self-attention + CTC in our ICASSP 2019 paper (https://arxiv.org/abs/1901.10055). Our implementation uses internal infra, so we're a ways from releasing code :(

Hoping paper details suffice and help with the parameter search, and happy to respond to questions over e-mail. Would love to see an open-source implementation with local or directed attention built out!

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#98

Post by toomuchtodo »

maxxxxx wrote: post #72
gruez wrote: post #67

Earlier quoted context omitted.

Yes

That's stupid. I do offline maps mainly for the times when I don't have a good connection. It makes no sense to lose the maps when you are spending an extended amount of time off-grid. That's exactly when you need offline maps.

License issues. Wouldn't happen if all the data was OpenStreetMap and Google data only.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#99

Post by propogandist »

penagwin wrote: post #12
Someone1234 wrote: post #4

Just to be clear: This has nothing to do with "Wake Words" (e.g. OK Google, Alexa, Hey Siri, etc) which have always been handled offline/locally. This is translating what you said after the wake word from voice to text on the local [Pixel] hardware rather than sending it into Google's Cloud. The biggest benefits here are speed and reliability. It could also handle some actions offline.

Another benefit is privacy, this eliminates an entire set of potentially personal data from being handed off to Google.

Gboard is governed by Google's catch all privacy policy, that allows them to gather all data and mine everything.

If you have an android device with Google services and a firewall, you'll see that the device is constantly phoning home, which is also noted in the privacy policy.

This does nothing for privacy, rather than provide the illusion of privacy.

Re: Google’s new voice recognition system works instantly and offline (Pixel only)

#100

Post by davidw »

davidw wrote: post #41

Call me when it can figure out my wife's Italian name, pronounced correctly :-(

Downvoter(s): sorry, but it's true. Google can't figure out my wife's name, which is pretty freaking lame, as she's the person I interact with the most in terms of sending messages and emails and whatnot.
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