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Training a predictor of emotional response based on explicit voting on content and eye tracking to verify attention

  • US 9,477,993 B2
  • Filed: 10/13/2013
  • Issued: 10/25/2016
  • Est. Priority Date: 10/14/2012
  • Status: Active Grant
First Claim
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1. A system configured to utilize eye tracking for collecting a naturally expressed affective response for training an emotional response predictor, comprising:

  • a memory storing computer executable modules; and

    a processor configured to execute the computer executable modules;

    the computer executable modules comprising;

    a label generator configured to receive first and second votes of a user on first and second segments of content consumed by the user, respectively;

    the label generator is further configured to utilize the first and second votes to generate first and second labels related to first and second emotional responses to the first and second segments, respectively;

    wherein the first and second votes are generated via a voting mechanism that comprises one or more of the following;

    a like voting mechanism, a dislike voting mechanism, a star rating mechanism, a numerical rating mechanism, an up voting mechanism, a down voting mechanism, and a ranking mechanism;

    a gaze analyzer configured to receive first and second eye tracking data of the user acquired while the user consumed the first and second segments, and to make a first determination that a first gaze-based attention level to the first segment reaches a first predetermined threshold, and to make a second determination that a second gaze-based attention level to the second segment does not reach a second predetermined threshold; and

    a sample generator configured to utilize the first and second determinations to assign, for purpose of training a measurement emotional response predictor, a higher weight to a first sample comprising the first label and a first affective response measurement of the user, than to a second sample comprising the second label and a second affective response measurement of the user;

    wherein the first measurement was taken by a sensor while the user consumed the first segment, and the second measurement was taken by the sensor while the user consumed the second segment.

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