An emotion estimating system includes a learning model and an estimation unit. The learning model accepts external information and biological information as input, and outputs an emotion of a user. The estimation unit changes a weighting applied to external information about the user detected by a first detector and a weighting applied to biological information about the user detected by a second detector in accordance with a situation around the user, and estimates the emotion output as a result of inputting external information and biological information changed by the respective weightings into the learning model as the emotion of the user.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An emotion estimating system, comprising: a learning model that accepts external information and biological information as input, and outputs an emotion of a user; and an estimation unit that changes a weighting applied to external information about the user detected by a first detector and a weighting applied to biological information about the user detected by a second detector in accordance with a situation around the user, and estimates the emotion output as a result of inputting external information and biological information changed by the respective weightings into the learning model as the emotion of the user. 2. The emotion estimating system according to claim 1, wherein the situation around the user is determined on a basis of environment information detected by a third detector that detects environmental information about an environment around the user. 3. The emotion estimating system according to claim 2, wherein if the estimation unit determines that the situation around the user is a public situation or a situation that tends to induce nervousness or stress, the estimation unit makes the weighting with respect to the biological information larger than the weighting with respect to the external information. 4. The emotion estimating system according to claim 2, wherein if the estimation unit determines that the situation around the user is a private situation or a situation that tends to induce relaxation or relief, the estimation unit makes the weighting with respect to the biological information smaller than the weighting with respect to the external information. 5. The emotion estimation system according claim 1, wherein if the estimation unit determines that the user has a personality type in which emotion is not readily exhibited in expression and behavior, the estimation unit makes the weighting with respect to the biological information larger than the weighting with respect to the external information. 6. The emotion estimating system according to claim 1, wherein if the estimation unit determines that the user has a personality type in which emotion is readily exhibited in expression and behavior, the estimation unit makes the weighting with respect to the biological information smaller than the weighting with respect to the external information. 7. An emotion estimating system, comprising: a plurality of learning models, each of which accepts external information and biological information as input, and outputs an emotion of a user; a selector that selects a learning model to use, in accordance with a situation around the user; and an estimation unit that estimates the emotion output as a result of inputting external information about the user detected by a first detector and biological information about the user detected by a second detector into the selected learning model as the emotion of the user. 8. The emotion estimating system according to claim 7, further comprising: a third detector that detects environmental information about an environment around the user, wherein the selector determines the situation around the user on a basis of the environmental information detected by the third detector. 9. An emotion estimating system, comprising: a learning model that accepts external information, biological information, and environmental information about an environment around a user as input, and outputs an emotion of the user; and an estimation unit that estimates the emotion output as a result of inputting external information about the user detected by a first detector, biological information about the user detected by a second detector, and environmental information about the environment around the user detected by a third detector into the learning model as the emotion of the user. 10. The emotion estimating system according to claim 1, wherein the first detector detects at least one of an expression and speech of the user as the external information, and the second detector detects at least one of skin potential and heart rate of the user as the biological information. 11. The emotion estimating system according to claim 1, wherein the first detector and the second detector are provided in an interactive robot. 12. The emotion estimating system according to claim 11, wherein environmental information about an environment around the user is detected by an environmental sensor installed near where the interactive robot is present. 13. The emotion estimating system according to claim 12, wherein the emotion estimating system includes a control server, the interactive robot transmits current position information to the control server, and the control server transmits, to the interactive robot, environmental information about the environment around the user acquired from an environmental sensor installed at a position corresponding to the current position information acquired from the interactive robot. 14. The emotion estimating system according to claim 13, wherein the control server requests the environmental sensor installed at a position corresponding to the current position information acquired from the interactive robot to acquire the environmental information about the environment around the user.