一种面向智能助理的多模态情感计算方法、系统及设备
By collecting multimodal signals and performing hierarchical encoding through intelligent assistant terminals, combined with cloud computing, the problem of insufficient accuracy and real-time performance of emotion recognition caused by single-modal signals in existing technologies has been solved, achieving more accurate and timely emotion perception and understanding, and reducing privacy and security risks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- KUAISHANGYUN (SHANGHAI) NETWORK TECHNOLOGY CO LTD
- Filing Date
- 2026-05-13
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for emotion computing in intelligent assistants rely on single-modal signals, resulting in insufficient accuracy and real-time performance in emotion recognition. Furthermore, the limited computing power of terminals or the large amount of data transmission in the cloud pose privacy and security risks.
Multimodal signal streams are collected through intelligent assistant terminals, time alignment and feature extraction are performed, low-latency sentiment computing is carried out using hierarchical encoders, and cloud computing is triggered when necessary. Deep sentiment computing is then performed by combining user long-term memory data from cloud servers.
It achieves a balance between the accuracy, real-time performance, and privacy security of emotion recognition, improves the depth and precision of emotion computing, and provides a more human-centered interactive experience.
Smart Images
Figure CN122220846B_ABST