5 results about "Expressed emotion" patented technology

An emotion recognition method includes the following steps: acquiring video data of a human-object interaction behavior process; performing data labeling on the positions of a person and an object and the interaction behaviors and emotions expressed by the person; constructing a feature extraction model based on deep learning, extracting features of interaction between the person and the object in a time-space dimension, and detecting the position and category of the human-object interaction behavior; mapping the detected interaction behavior category into a vector form through a word vector model; and finally, constructing a fusion model based on deep learning, fusing the interaction behavior vector and the time-space interaction behavior features, and identifying the emotion expressed by the interaction person.

To express emotions that are more lifelike. [Solution] The robot 100 is equipped with a control unit 110 that acquires external information using sensors, acquires the internal state of the robot body, sets a third emotion determined based on a first emotion or a first emotion change degree determined based on the external information and a second emotion or a second emotion change degree determined based on the internal state, as a simulated emotion of the robot 100, and controls the operation of the robot 100 based on the set simulated emotion.

An object of the system according to the embodiment is to allow a user to anonymously express an emotion and receive mental health care without anxiety.SOLUTION: A system according to an embodiment includes an emotion expression unit, a virtual space providing unit, a color scheme customization unit, a history deletion unit, and a mental health service providing unit. The emotion expression unit anonymously expresses an emotion. The virtual space providing unit processes the feeling expressed by the feeling expression unit. The color scheme customizing unit customizes the color scheme of the virtual space provided by the virtual space providing unit. The history deletion part deletes the history of the feeling expressed by the feeling expression part. The mental health service providing unit provides a professional mental health service based on the emotion expressed by the emotion expression unit.SELECTED DRAWING: Figure 1

The present disclosure relates to the recognition of emotion in speech, both what is said and how it is said and the detection of a possible concordance or discrepancy between the two. A method is described for generating a time-stamped history of emotions a user reports by voice along with emotions detected automatically from those voice reports. A user utterance is analyzed using speech-to-text processing and a natural-language processing model to determine the emotion the user reports feeling. The user utterance is also analyzed using acoustic analysis to detect the emotion expressed in the user's voice report. A harmony report is generated from the time-stamped reports of concordance and discrepancy to measure the extent to which the user's perception of their emotions agrees with the emotions detected. The purpose of the invention is to provide insight into a user's emotions in real time and over time.

The invention discloses an active listening emotion support reply generation method and system oriented to implicit demand perception, relates to the technical field of natural language processing, and aims to solve the problem that an existing method usually only pays attention to identification and pacification of dominant emotions of a user and lacks in-depth understanding and active response ability to implicit demands. In order to solve the problem of difficulty in obtaining accurate emotion support reply due to the fact that the emotion support reply is difficult to obtain, the invention applies to gradually mine deep psychological causes of a user and extract potential demand information by performing multi-level reasoning on emotion expression and semantic clues input by the user. The overall framework comprises a listening stage and a suggestion stage, the listening stage guides a user to more truly express emotion and intention through an active listening strategy, and the suggestion stage generates targeted and common emotion support reply according to the identified implicit demand. According to the method, dynamic processing from surface emotion to deep demand is realized in combination with an inference chain mechanism, and the method has continuous emotional sharing ability and personalized response characteristics. And accurate emotion support reply can be obtained.