Raspberry Pi Robot That Reads Your Emotions

It’s getting easier and easier to add machine intelligence to your hacks, even to the point where you sometimes don’t have to install any special software. In this case [Dexter Industries] has added the ability to read human emotions to their EmpathyBot robot by making use of Google Cloud Vision.

Press a button on the robot and it moves forward until it’s a certain distance from an object. It then takes a picture and sends it off to Google Cloud Vision along with a request to do face detection. The response that Google returns is in JSON format and, if it finds a face, includes the likelihood of the face being happy, sad, sorrowful or surprised. The robot parses that response and gives an appropriate canned speech using the text-to-speech software, eSpeak e.g. “You seem happy! Tell me why you are so happy!”.

[Dexter] has made the source code available on github. It’s written in python and is easy to read by anyone with even just a little programming experience. The video after the break gives a number of demonstrations, including some with non-human subjects.

On their webpage, [Dexter Industries] also gives a little further analysis. For example, one subject had facial hair which gave Google difficulty with interpreting the emotion. But after some trimming, interpretation improved. It did have difficulty with a baby though, possibly due to chubby cheeks.

We recently saw other examples of hacks using machine intelligence software. [Dexter] has used Google Cloud Vision before for sorting candy. And before that it was Google’s Tensorflow being used by a robot to recognize and say the names of objects around a garage.

8 thoughts on “Raspberry Pi Robot That Reads Your Emotions

  1. After the last 3 attempts I did at getting something sensible from webpages showcasing Google AI I have little trust left in Google’s prowess at tackling that subject.
    And I’m pretty happy about that, the last thing I want is capable AI from Google, since that will be used against everybody of course.

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