Text-driven advertisement video generation method based on emotion feedback

By collecting user multi-modal emotional feedback data in real time and dynamically adjusting the advertising video content, the problem that traditional advertisements cannot dynamically adjust according to the user's emotional status is solved, and the advertising effect with high participation and conversion rate is achieved.

CN119697442APending Publication Date: 2025-03-25WUXI UNIV
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Patent Information

Application Number
CN202411816812.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-11
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

Traditional video ads cannot be dynamically adjusted based on the audience's personalized needs and emotional status, resulting in limited user engagement and advertising conversion rates.

Method used

The text-driven advertising video generation method based on emotional feedback is adopted, and the advertising copy is converted into an initial video through the text generation model, and the user's multi-modal emotional feedback data is collected in real time, and the deep learning model is used to extract and fusion features, and the video content is dynamically adjusted until the user's emotional participation is maximized.

Benefits of technology

It achieves a high degree of compatibility between advertising videos and users' emotional status, improves user participation and advertising conversion rate, and enhances the attractiveness and marketing effect of advertising.

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Abstract

The invention discloses a text-driven advertisement video generation method based on emotion feedback, relates to the technical field of digital advertisement and man-machine interaction, and aims to dynamically adjust advertisement content and improve individuation, interactivity and conversion rate by collecting emotion data such as facial expression, voice features and eye movement tracks of a user in real time. A text generation video model and a multi-mode emotion recognition technology are combined, and feature fusion and feedback processing are utilized, so that the advertisement video better conforms to the emotion of the user; multi-round feedback and self-adaptive optimization ensure that advertisements transmit core information and flexibly respond to user emotional states at the same time, attraction and participation degree are greatly improved, an innovative feature fusion algorithm further improves individuation and real-time response capability of generated videos, a brand new solution is provided for the field of digital advertisements, and the method is suitable for popularization and application. And the development of individuation and emotional interaction is promoted.
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