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posted by martyb on Thursday July 20 2017, @08:02AM   Printer-friendly
from the speak-up! dept.

Mozilla wants to crowdsource thousands of hours of voice recordings for an open source voice recognition engine:

The Mozilla Foundation launched "Common Voice," which is a crowdsourced initiative to build an open source data set for voice recognition applications.

Many technology companies believe that voice control will be embedded into most devices in the future. This is why Apple, Google, Amazon, Microsoft, Baidu, and others are all trying to put their own voice-controlled artificial intelligence assistants into as many devices as they can and as fast as they can, in order to gain market share before the competition.

The problem with this, according to Mozilla, is that voice controlled technologies could end up being dominated by proprietary technology and data sets, which aren't made available to startups and academics. As some large companies already benefit from billion-dollar revenues, it could later become too difficult for startups to catch up with the big players. Though[sic] Common Voice, Mozilla aims to democratize voice recognition technology.

You could use this to build (the easy part of) a personal assistant that either does not use the cloud, or does so on your terms.


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  • (Score: 3, Informative) by rob_on_earth on Thursday July 20 2017, @01:47PM (1 child)

    by rob_on_earth (5485) on Thursday July 20 2017, @01:47PM (#541904) Homepage

    I have discussed this with people before and the all say "but you have to train it".
    I do not care if I have to train it I just want the basic functionality some people (sadly not me) had using Dragon, even on Linux using a complex shim.
    Preferably I want it to work on a Raspberry Pi without any network connectivity.
    I also do not need 100% reliability.

    Too much to ask?

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  • (Score: 0) by Anonymous Coward on Thursday July 20 2017, @10:18PM

    by Anonymous Coward on Thursday July 20 2017, @10:18PM (#542083)

    Does the Pi have the computational power to handle this? I have never looked at language processing so no idea about the overhead.