Hearing, but not for control. For segment cuts to be associated with
image cuts (e.g. 'red numbers').

Also, the red numbers should not be sourced by any kind of turking (such
as the color channel threshold kind of is). Instead a hard or soft
focusing should source the image portion of interest.

As one would bring an apple in front of a child's eyes and say "Apple"
or "An apple" ...

Such a set-up would be unsupervised enough (no text in the database and
no other kind of turking/ annotation), but instead an association
between an image db (where non-OCRed text can be included) and a sound
cuts db (where spoken text could also be included). The learning model
can be complex enough so that a spoken phrase that describes the apple
fruit to be linked (or associated) not to an image but to only a tiny
segment of the same spoken phrase (the 'apple' noun, when isolated).

So, instead of sourcing for control, the hearing module should source to
a smart association algorithm that runs continuously (so that
associations can be made at discrete times).


On 19.08.2019 15:37, Stefan Reich via AGI wrote:
You mean voice control? Yeah I have code for that.

On Mon, 19 Aug 2019 at 05:54, Secretary of Trades
<[email protected] <mailto:[email protected]>> wrote:

    It sees. It must also hear.


    On 19.08.2019 01:31, Stefan Reich via AGI wrote:
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