Dynamic Ad Generation via NLP Segment Assembly
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Solution Overview
Problem
Current methods for generating mobile advertisements are costly and time-consuming, requiring manual selection and production of polished audio/visual presentations, resulting in a limited number of new ads being produced over a given period.
Innovation Solution
A dynamic content generation system using natural language processing (NLP) that analyzes user input to create unique, production-quality audio/visual presentations in real-time, based on customer feedback, by selecting and assembling pre-generated audio and video segments from a database, allowing for a large variety of new ads to be generated efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual selection and production of polished audio/visual presentations is used, then production quality is improved, but production cost and time increase
Solution Approach 1:
The patent segments the advertisement production process into modular components: a database of pre-produced audio segments, video segments, and transition segments. These segments are stored and can be individually selected and combined through NLP-driven automation, enabling high-quality production without manual intervention in the assembly process.
Solution Approach 2:
The patent applies preliminary action by pre-producing and storing audio, video, and transition segments in a database before the actual advertisement generation. This allows the system to rapidly assemble high-quality advertisements by combining pre-prepared elements, eliminating the need for manual production of each ad while maintaining polished quality.
2Manufacturing precision
If manual selection and production methods are used, then production quality is improved, but the number of ads produced decreases
Solution Approach 1:
The system performs self-service by using NLP to automatically analyze customer feedback, select appropriate audio/video/transition segments from the database, and assemble complete advertisements without human intervention. This automation enables the generation of billions of unique ads while maintaining consistent quality standards through systematic segment selection and combination.
Solution Approach 2:
The patent changes parameters by transforming unstructured customer feedback text into structured selection criteria through NLP processing. The system extracts key parameters from feedback (sentiment, topics, key phrases) and uses these to dynamically select and combine segments, enabling mass production of customized ads with varying parameters while maintaining quality.
3Productivity
If NLP-based dynamic content generation is used, then productivity is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary NLP processing layer that bridges customer feedback and segment selection. This intermediary translates unstructured feedback into structured selection parameters, simplifying the overall system architecture by handling the complexity of natural language interpretation in a dedicated module rather than distributing it throughout the entire system.
4Adaptability or versatility
If manual advertisement production is used, then customization is limited, but production cost decreases
Solution Approach 1:
The patent applies local quality by allowing different segments (audio, video, transitions) to have different characteristics and styles within the same advertisement. The NLP system selects segments with locally optimized qualities that match specific portions of customer feedback, enabling highly customized advertisements where each segment is tailored to its specific context while maintaining overall production efficiency.
Data Source
AI summary
Apparatus and method for using natural language processing (NLP) to generate dynamic content, such as but not limited to an audio/visual (A/V) presentation. In accordance with some embodiments, a language analysis module is adapted to analyze a data signal received into a memory. The data signal is generated responsive to an input sequence expressed in a natural language format by a user of a network accessible device. A database of informational segments is stored in a memory, and a compositing engine is adapted to generate an on-the-fly presentation from selected segments in the database and to transmit the presentation as a unique display sequence for the user responsive to the input text sequence.