10 ms·

> Utter hogwash. The voice activation is a form of user input, nothing more. By that same logic, you could argue that use of a keyboard is explicit consent to h

> Utter hogwash. The voice activation is a form of user input, nothing more. By that same logic, you could argue that use of a keyboard is explicit consent to have all keystrokes recorded It's like typing in to a search engine, which these days means live streaming results. Seems you are empowering them to analyze those search inputs just the same.

MereInterest 8y ago
The type and amount of data transmitted, and the type and amount of data preserved depend on what is being done. Exceeding the minimum amount of data transmitted/preserved is a violation of privacy. - Case 1: local action, such as playing music, making a calendar event, setting an alarm. These have no need to be sent to - Case 2: remote action, such as performing a search. The audio can be parsed locally, with the search terms then sent externally to get the results. In neither case is it necessary to send the raw audio anywhere. In neither case is it necessary to record the audio for future use.
- maxxxxx 8y ago
  Totally agree. The raw audio shouldn't be sent back or at a minimum not stored.
  - sokoloff 8y ago
    The speech recognition is running remotely, only wakeword recognition is local on most of the devices.
    - TeMPOraL 8y ago
      Which is really a problem that needs to be solved. Just because it's cheaper to do something in the cloud, doesn't mean it should be done in the cloud.
      - sokoloff 8y ago
        IMO, it's cheaper and (importantly) better to do it in the cloud. Better in there's steady improvement to customer experience with zero customer interaction, a cleaner developer "apps" marketplace, and each local device can be smaller, cheaper, and lower power.
        TeMPOraL 8y ago
        Except that fully local tasks now cannot be done fully locally, more data than needed for the task is leaked to the service provider, and the whole thing becomes a centralized ordeal. It turns into a single service what should be a product giving access to mulitple services. It offers degraded user experience due to latency (reason #1 I don't use voice assistants, #2 being not much useful to be done with them if I can't trivially write code gluing them with stuff I have in my house), stops working completely when there's not Internet connection (Internet isn't and can never be as reliable as power), and I'm doubtful of how significant power benefits are once you account for the power that's used by various routers to transmit your voice to the cloud and get the results back.
        sokoloff 8y ago
        Power and cost benefits from the perspective of the end user. I have a device that draws under 10W that is (as far as I'm concerned) capable of world-class and ever-improving voice recognition and interaction. That a service provider or set of service providers are providing me temporary use of kilowatts of computing computing power that I don't ever see a bill for is irrelevant from the perspective of "is it worth me paying $40 and $5 of electricity per year to have a tiny voice assistant?" vs "is it worth me paying $500 and $75/year in power for a fully local, larger, and inferior solution?" It's unsurprising to me that the market evolved towards the former as the latter would almost surely be a commercial failure.
        TeMPOraL 8y ago
        I'm not surprised by the way the market evolved either, but I consider it a bug, not a feature. I'm a firm believer that if something is to be done, it deserves at least an attempt at doing it right. The product version would be a commercial failure only because it has to compete with the service version; the story would be different if the service version wasn't allowed to exist in the first place. Also let's not overestimate the involvement of the cloud in the actual voice recognition. With ML models, it's the training of a model that's expensive, not the actual use of that model. I don't see a reason why voice models, once trained, couldn't be run on the device, at a slightly increased cost of compute (of which phones have plenty). It would be fair and good engineering to provide models in exchange for payment. And no, I don't buy "it's not that simple", because I've worked with MS Speech API over a decade ago, on much slower hardware and on a shitty microphone I soldered myself from parts, and it did work well enough in "fixed grammar" mode after a bit of training with various sources of background noise (read: very loud music). I don't believe there's any technical obstacle; the decision to run this in a cloud is a purely business one, and like many modern business models, this one is geared towards extracting value from purported customers, not giving value to them.
- microcolonel 8y ago
  > The audio can be parsed locally Speech recognition doesn't work like that, there's no yacc/lex for you to just "run locally". Device-local recognition is limited, and not very agile. It often takes years for it to recognize new words, and it usually has extreme bias toward a handful of urban centres. I don't like sending my data away, and I choose not to, but it is simply not realistic to expect Google-quality or Amazon-quality continuous real time speech recognition and nlp to happen entirely on-device.
  - stordoff 8y ago
    > Speech recognition doesn't work like that, there's no yacc/lex for you to just "run locally" Why not? It _could_: > In our recent paper, "Streaming End-to-End Speech Recognition for Mobile Devices", we present a model trained using RNN transducer (RNN-T) technology that is compact enough to reside on a phone. This means no more network latency or spottiness — the new recognizer is always available, even when you are offline. [...] > The RNN-T we trained offers the same accuracy as the traditional server-based models https://ai.googleblog.com/2019/03/an-all-neural-on-device-speech.html https://ai.googleblog.com/2019/03/an-all-neural-on-device-sp...
    - macawfish 8y ago
      This is really cool!
    - TeMPOraL 8y ago
      > Why not? It _could_: It did. Anyone remembers the good ol' Microsoft Speech API of ~Windows 2000/XP era?
  - michaelmrose 8y ago
    You can already run an offline google translate that will not only recognize your words but translate it to a foreign language.
  - deleted 8y ago
    [deleted]
  - 8y ago

MereInterest 8y ago

The type and amount of data transmitted, and the type and amount of data preserved depend on what is being done. Exceeding the minimum amount of data transmitted/preserved is a violation of privacy. - Case 1: local action, such as playing music, making a calendar event, setting an alarm. These have no need to be sent to - Case 2: remote action, such as performing a search. The audio can be parsed locally, with the search terms then sent externally to get the results. In neither case is it necessary to send the raw audio anywhere. In neither case is it necessary to record the audio for future use.

maxxxxx 8y ago
Totally agree. The raw audio shouldn't be sent back or at a minimum not stored.
- sokoloff 8y ago
  The speech recognition is running remotely, only wakeword recognition is local on most of the devices.
  - TeMPOraL 8y ago
    Which is really a problem that needs to be solved. Just because it's cheaper to do something in the cloud, doesn't mean it should be done in the cloud.
    - sokoloff 8y ago
      IMO, it's cheaper and (importantly) better to do it in the cloud. Better in there's steady improvement to customer experience with zero customer interaction, a cleaner developer "apps" marketplace, and each local device can be smaller, cheaper, and lower power.
      - TeMPOraL 8y ago
        Except that fully local tasks now cannot be done fully locally, more data than needed for the task is leaked to the service provider, and the whole thing becomes a centralized ordeal. It turns into a single service what should be a product giving access to mulitple services. It offers degraded user experience due to latency (reason #1 I don't use voice assistants, #2 being not much useful to be done with them if I can't trivially write code gluing them with stuff I have in my house), stops working completely when there's not Internet connection (Internet isn't and can never be as reliable as power), and I'm doubtful of how significant power benefits are once you account for the power that's used by various routers to transmit your voice to the cloud and get the results back.
        sokoloff 8y ago
        Power and cost benefits from the perspective of the end user. I have a device that draws under 10W that is (as far as I'm concerned) capable of world-class and ever-improving voice recognition and interaction. That a service provider or set of service providers are providing me temporary use of kilowatts of computing computing power that I don't ever see a bill for is irrelevant from the perspective of "is it worth me paying $40 and $5 of electricity per year to have a tiny voice assistant?" vs "is it worth me paying $500 and $75/year in power for a fully local, larger, and inferior solution?" It's unsurprising to me that the market evolved towards the former as the latter would almost surely be a commercial failure.
        TeMPOraL 8y ago
        I'm not surprised by the way the market evolved either, but I consider it a bug, not a feature. I'm a firm believer that if something is to be done, it deserves at least an attempt at doing it right. The product version would be a commercial failure only because it has to compete with the service version; the story would be different if the service version wasn't allowed to exist in the first place. Also let's not overestimate the involvement of the cloud in the actual voice recognition. With ML models, it's the training of a model that's expensive, not the actual use of that model. I don't see a reason why voice models, once trained, couldn't be run on the device, at a slightly increased cost of compute (of which phones have plenty). It would be fair and good engineering to provide models in exchange for payment. And no, I don't buy "it's not that simple", because I've worked with MS Speech API over a decade ago, on much slower hardware and on a shitty microphone I soldered myself from parts, and it did work well enough in "fixed grammar" mode after a bit of training with various sources of background noise (read: very loud music). I don't believe there's any technical obstacle; the decision to run this in a cloud is a purely business one, and like many modern business models, this one is geared towards extracting value from purported customers, not giving value to them.
microcolonel 8y ago
> The audio can be parsed locally Speech recognition doesn't work like that, there's no yacc/lex for you to just "run locally". Device-local recognition is limited, and not very agile. It often takes years for it to recognize new words, and it usually has extreme bias toward a handful of urban centres. I don't like sending my data away, and I choose not to, but it is simply not realistic to expect Google-quality or Amazon-quality continuous real time speech recognition and nlp to happen entirely on-device.
- stordoff 8y ago
  > Speech recognition doesn't work like that, there's no yacc/lex for you to just "run locally" Why not? It _could_: > In our recent paper, "Streaming End-to-End Speech Recognition for Mobile Devices", we present a model trained using RNN transducer (RNN-T) technology that is compact enough to reside on a phone. This means no more network latency or spottiness — the new recognizer is always available, even when you are offline. [...] > The RNN-T we trained offers the same accuracy as the traditional server-based models https://ai.googleblog.com/2019/03/an-all-neural-on-device-speech.html https://ai.googleblog.com/2019/03/an-all-neural-on-device-sp...
  - macawfish 8y ago
    This is really cool!
  - TeMPOraL 8y ago
    > Why not? It _could_: It did. Anyone remembers the good ol' Microsoft Speech API of ~Windows 2000/XP era?
- michaelmrose 8y ago
  You can already run an offline google translate that will not only recognize your words but translate it to a foreign language.
- deleted 8y ago
  [deleted]
- 8y ago