Method for assessing expressiveness based on multi-modal data and computing device

By collecting and fusing multimodal data, the problem of lack of objective quantification in traditional evaluation methods has been solved, enabling a comprehensive and personalized evaluation of user performance and generating multi-dimensional evaluation reports.

CN122196877APending Publication Date: 2026-06-12HENAN QINWEI DIGITAL TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HENAN QINWEI DIGITAL TECHNOLOGY CO LTD
Filing Date
2026-02-12
Publication Date
2026-06-12

AI Technical Summary

⚠Technical Problem

Traditional performance evaluation methods lack objective quantitative basis and are difficult to fully reflect the dynamic behavioral characteristics and true performance level of users in different business scenarios, especially in multi-user scenarios where accurate evaluation is difficult to achieve.

⚗Method used

An evaluation method based on multimodal data is adopted. Through the collaborative work of servers and terminal devices, audio and video data of target users are collected. Audio, text and video features are extracted using feature recognition models, and weighted fusion is performed based on data collection patterns and user information to generate an evaluation report.

🎯Benefits of technology

It enables a comprehensive and objective assessment of target user performance, allows for multi-dimensional evaluation of business performance, generates personalized assessment reports, and improves the accuracy and practicality of the assessment.

✦ Generated by Eureka AI based on patent content.

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Abstract

The embodiment of the application relates to the field of artificial intelligence technology, and provides a performance evaluation method based on multi-modal data and a computing device, which is applied to a server, the server is in communication connection with a terminal device, and the method comprises the following steps: in response to receiving a service practice instruction sent by the terminal device, determining a data acquisition mode and user information based on a service database; acquiring multi-modal data of a target user by using the terminal device based on the data acquisition mode; analyzing the multi-modal data; obtaining fusion weights corresponding to audio features, text features and video features; weighting and fusing each feature based on the fusion weights to obtain fusion features; and generating an evaluation report of the target user according to the fusion features. Based on the scheme, the server can acquire multi-modal data of the target user by using the terminal device, and can realize comprehensive and objective evaluation of the performance of the target user through feature analysis and feature fusion of the multi-modal data, so that the performance evaluation effect of the target user is optimized.
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