5 results about "Emotion detection" patented technology

This invention provides a method and system for rapid detection of emotions induced by VR gory scenes based on electroencephalography (EEG), belonging to the field of EEG emotion detection technology. Subjects wear virtual reality devices connected to an 8-channel EEG acquisition device to obtain raw EEG signals with scene time stamps. Time-windowed EEG data is obtained through preprocessing and time window segmentation. Low-frequency energy features are calculated in the 1-10Hz frequency band, and phase coupling features between EEG channels are extracted based on a 2Hz narrowband segmentation. The coupling relationship is distinguished into contralateral long-distance and ipsilateral short-distance coupling based on scalp spatial location, and their intensity features are statistically analyzed. The low-frequency energy features and the long- and short-distance coupling strengths are constructed as composite discriminative features and input into a discriminative model to achieve rapid detection of gory scenes, improving the timeliness, objectivity, and accuracy of emotion recognition.

The application relates to a voice call detection method, a voice call detection device, computer equipment and a storage medium. The method comprises the following steps: when a customer service agent carries out voice call for a financial service in processing, acquiring voice audio generated by the customer service agent and call text corresponding to the voice audio; extracting audio features from the voice audio and text features from the call text; respectively carrying out quality detection processing on the audio features and the text features to obtain emotion detection results for the audio features and text detection results for the text features; the quality detection processing is used for quality evaluation on voice emotion expressed by the audio features and quality evaluation on text meaning expressed by the text features; and based on the emotion detection results and the text detection results, call detection results for the voice audio are obtained. The method can improve the efficiency of voice call detection and improve the accuracy of voice call detection.

This invention discloses an intelligent method and system for generating educational content, relating to the field of content generation technology. An intelligent educational content generation system includes: a needs acquisition module, a student knowledge graph generation module, an intelligent content generation module, an emotional content optimization module, a learning community optimization module, and a content protection module. This invention collects students' learning needs information, generates personalized needs reports, and constructs student knowledge graphs based on these needs; it uses an intelligent educational content generation model to tailor interdisciplinary learning content with dynamically adjusted difficulty for each student, effectively improving learning efficiency and experience; and through real-time emotion detection and learning community optimization, it meets students' learning needs and pays attention to their emotional state, enhancing students' learning motivation and engagement, and contributing to the achievement of more comprehensive learning goals.

Provided in the present application are a detection method and a related apparatus. In the method, an emotion reference value of a user himself / herself may be first calculated by means of historical physiological data of the user, and then an emotion detection result of the user is determined by means of real-time physiological data and the emotion reference value of the user. When the emotion detection result indicates that the emotion of the user is an abnormal emotion, an abnormal-emotion prompt and an early warning may also be given in a timely manner, and corresponding emotional health improvement solutions can be used for different emotional health risk results. In this way, the emotion of the user is first recognized by means of the emotion reference value of the user himself / herself, such that an abnormal change in the emotion of the user can be recognized more accurately, thereby improving the perception of the user for his / her degree of emotional fluctuation, and reducing emotional health risks of the user.

The application discloses a student psychological state detection method based on a feature interaction learning network, which comprises the following steps: obtaining facial expression video data and heart rate data of a test object when the test object watches a plurality of test videos with a single emotional feature; performing feature extraction on the facial expression video data and the heart rate data to obtain facial expression emotional features and heart rate features of the test object; fusing the facial expression emotional features and the heart rate features, and performing emotion recognition based on the fusion result to obtain an emotional category corresponding to each sample video; comparing an emotional feature label corresponding to each test video with the emotional category thereof, and combining comparison results of the test videos and a preset threshold condition to generate an emotion detection result of the test object. The application fuses facial expressions and heart rate signals to perform emotion recognition, improves the accuracy of emotion recognition and classification, and provides a scientific basis and support for college student psychological health state prediction, emotion management and intervention treatment.