一种采用智能生成技术实现的网播方法及系统
By obtaining the target broadcast duration of podcast programs, identifying content types, and constructing semantic dependency topology graphs, the problems of broadcast accuracy and content coherence in the automated production of podcast programs are solved, achieving efficient duration compression and complete information broadcasting effects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JIANGSU BROADCASTING CORPORATION
- Filing Date
- 2026-04-10
- Publication Date
- 2026-07-17
AI Technical Summary
In the automated production of podcast programs, existing technologies based on linear pipelines with basic character counting struggle to achieve broadcast accuracy and content coherence, resulting in deviations in actual rendering time and logical breaks, failing to meet the demands for high-concurrency, high-quality intelligent audio broadcasting.
By acquiring the target broadcast duration, content type identification and semantic dependency topology graph construction are performed to achieve semantically perceptive truncation processing and generate compensatory closing text, ensuring the logical coherence and information integrity of the broadcast content.
It improved the accuracy of the predicted duration of broadcast content, ensured the logical coherence and semantic consistency of the broadcast content after truncation, and effectively enhanced the integrity of information and the sense of structural integrity.
Smart Images
Figure CN121999759B_ABST