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Author Topic: Voice to Text software  (Read 7623 times)

AArdvark

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Re: Voice to Text software
« Reply #15 on: November 09, 2015, 12:32:02 PM »

My phone has 4 microphones, probably for a similar reason, though I don't use voice commands. It in theory improves the quality of phone calls too.

That is interesting, I wasn't aware that multiple microphones were 'old hat'. :-[

It does however beg the question... What is that enables Apple's Siri to work so well, no training or separate mic's required, when the rest of the industry remains so useless and feeble?

It is not just better hardware, although a cleaner input helps.
The reason it works so well is that it is using huge and complex model(s) that have been trained on millions of peoples voices/inputs and is constantly being improved as it is used.
It is the same idea that MS is using with their Voice Recognition via Cortana.

It is also the reason why Banking Voice Recognition works well because the model is big and the dictionary is small and specific to the needs of the bank.
(Also likely to be running on the mainframe and/or be dedicated hardware.)

I would bet that there is a bit of custom hardware in there somewhere to speed up the searching and matching at Apple also.
(I am sure Apple could 'throw' something together costing 'loose change'  ;D )
Don't forget this is done in multiple languages as well, so it will be some big backend.

Maybe on second thoughts, it is better hardware ...... but at both ends.  ;D ;D
 
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sevenlayermuddle

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Re: Voice to Text software
« Reply #16 on: November 09, 2015, 02:02:16 PM »

With hindsight I regret being so critical of other (than Apple) systems as in all honesty my experiences are out of date.  :-[

Sticking with Apple, and despite the fact I'm beginning to sound like a one-man advertising campaign, I wonder whether one reason it is becoming really quite good is that they are turning out devices that strongly encourage real-world use of the technology?

People worry, of course, over the privacy issues of voice data being uploaded and stored on servers.  But the upside of that is, I'd imagine, that the more the more the system is used, the better it will get?   If so, then providing a system where voice recognition actually fills a need, with strong incentives to use it, ought to make for a better system.  :-\

The Apple Watch wouldn't be a great deal of use without Siri IMHO, and so it does get used.  And with the new TV, quite apart from searching for films etc by name, justifies itself from the simple ability to say things like 'rewind 25 seconds' during film playback.  Even over the *background sound from the film's soundtrack (and I have a very beefy sound system), it works very reliably indeed and quickly becomes second nature for playback control, so it actually gets used too.

edit... * fair to admit, it does seem to reduce the playback volume somewhat during speech input. Still impressive though.
« Last Edit: November 09, 2015, 02:09:15 PM by sevenlayermuddle »
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AArdvark

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Re: Voice to Text software
« Reply #17 on: December 09, 2015, 03:31:31 AM »

From yet more 'random reading' on the InterWebs!!  ;D

Here is some 'Technical' info covering the latest sort of software\methods used for Voice recognition etc (Probably very similar at MS, Google & Apple)

http://googleresearch.blogspot.co.uk/2015/08/the-neural-networks-behind-google-voice.html

Deep Learning in Neural Networks: An Overview by Jürgen Schmidhuber
[From http://people.idsia.ch/~juergen/deep-learning-overview.html ]
(Paper here --> http://www.idsia.ch/~juergen/DeepLearning8Oct2014.pdf)

Quote
Abstract. In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the previous millennium. Shallow and deep learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

Enough references to keep anyone occupied for the next 6 months at least.  :D :D
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