Information processing method, information processing device, and program

Abstract

To extract, with high accuracy, content that elicits a prescribed emotion in a user.SOLUTION: An information processing method causes a processor included in an information processing device to execute the steps of: extracting prescribed content that elicits a prescribed emotion in a prescribed user from a content list on the basis of an elicitation level predicted by a content model; sequentially acquiring brainwave signals of the prescribed user stimulated by the prescribed content from a brainwave measurement device worn by the prescribed user; inputting the sequentially acquired brainwave signals to a brainwave model that predicts the elicitation level of the prescribed emotion in the prescribed user by the content during stimulation by inputting the brainwave signal of the prescribed user stimulated by the content to predict the elicitation level of the prescribed emotion caused by the prescribed content; and updating the content model that predicts the elicitation level by inputting feature amounts of the content, using the correspondence between the feature amounts of the prescribed content and the elicitation level predicted by the brainwave model as re-learning data.SELECTED DRAWING: Figure 9

Claims

1. The processor included in the information processing device The process involves sequentially acquiring the brainwave signals of a designated user stimulated by a designated content from an electroencephalogram (EEG) measurement device attached to the designated user, The brainwave model, which receives the brainwave signals of a predetermined user stimulated by the content and predicts the degree to which the content stimulates the predetermined user to evoke nostalgia or anger, receives the brainwave signals acquired in the order described above and predicts the degree to which the predetermined content evokes nostalgia or anger. The correspondence between the features of the predetermined content and the degree of arousal predicted by the electroencephalogram model is used as retraining data to update the content model that predicts the degree of arousal by inputting the features of the content. From the content list, extract predetermined content that evokes nostalgia or anger in the predetermined user based on the degree of triggering predicted by the content model, A program that executes the command.

2. The aforementioned processor, The feature quantities of each of the multiple candidate contents in the content list are input into the content model, and based on the predicted triggering degree of each of the multiple candidate contents, the triggering score for each of the multiple candidate contents is calculated. The extraction includes, based on the calculated trigger score, extracting predetermined content from among the plurality of candidate content that triggers nostalgia or anger in the predetermined user, Acquiring in the order described above includes sequentially acquiring the brainwave signals of the predetermined user being stimulated by the predetermined content extracted, The program according to claim 1.

3. The calculation described above includes recalculating the trigger score based on the updated content model, The extraction includes re-extracting predetermined content from the plurality of candidate content based on the recalculated trigger score, The processor further causes the recalculation, re-extraction, and updating to be repeated. The program according to claim 2.

4. The program according to claim 2 or 3, wherein the extraction includes extracting at least one of the predetermined content having an elicitation score greater than or equal to a predetermined value and the predetermined content having an elicitation score less than or equal to a predetermined value.

5. The program according to claim 2, wherein the calculation further includes calculating the trigger score based on the similarity between the content that evokes nostalgia or anger in a predetermined user, which is included in the training data used when the content model is trained, and candidate content in the content list.

6. The program according to any one of claims 1 to 3, wherein the content model is generated based on the correspondence between the feature quantities of at least one selected content selected by the predetermined user as content that evokes nostalgia or anger, and the evaluation of the nostalgia or anger by the predetermined user stimulated by the at least one selected content, and the correspondence between at least one non-selected content not selected by the predetermined user and the evaluation of the nostalgia or anger by the predetermined user stimulated by the at least one non-selected content.

7. The program according to claim 6, wherein the electroencephalogram model is generated based on the correspondence between the electroencephalogram signals of a predetermined user stimulated by the at least one selected content and the labels relating to nostalgia or anger corresponding to the at least one selected content, and the correspondence between the electroencephalogram signals of a predetermined user stimulated by the at least one non-selected content and the labels relating to nostalgia or anger corresponding to the at least one non-selected content.

8. The processor identifies, based on the updated content model, the content features that evoke nostalgia or anger in the predetermined user. A program according to any one of claims 1 to 3, further comprising generating predetermined content that stimulates a predetermined user based on the identified features.

9. The program according to claim 8, which further causes the processor to include the generated content in the content list.

10. An information processing device including a processor, The aforementioned processor, The process involves sequentially acquiring the brainwave signals of a designated user stimulated by a designated content from an electroencephalogram (EEG) measurement device attached to the designated user, The brainwave model, which receives the brainwave signals of a predetermined user stimulated by the content and predicts the degree to which the content stimulates the predetermined user to evoke nostalgia or anger, receives the brainwave signals acquired in the order described above and predicts the degree to which the predetermined content evokes nostalgia or anger. The correspondence between the features of the predetermined content and the degree of arousal predicted by the electroencephalogram model is used as retraining data to update the content model that predicts the degree of arousal by inputting the features of the content. From the content list, extract predetermined content that evokes nostalgia or anger in the predetermined user based on the degree of triggering predicted by the content model, An information processing device that performs the following actions.

11. The processor included in the information processing device The process involves sequentially acquiring the brainwave signals of a designated user stimulated by a designated content from an electroencephalogram (EEG) measurement device attached to the designated user, The brainwave model, which receives the brainwave signals of a predetermined user stimulated by the content and predicts the degree to which the content stimulates the predetermined user to evoke nostalgia or anger, receives the brainwave signals acquired in the order described above and predicts the degree to which the predetermined content evokes nostalgia or anger. The correspondence between the features of the predetermined content and the degree of arousal predicted by the electroencephalogram model is used as retraining data to update the content model that predicts the degree of arousal by inputting the features of the content. From the content list, extract predetermined content that evokes nostalgia or anger in the predetermined user based on the degree of triggering predicted by the content model, An information processing method that performs the following.

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