Contextual Content Querying Using Multimodal Rendering Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing content retrieval methods rely heavily on manual data entry or single modality inputs, leading to increased resource usage and decreased precision, especially in noisy environments with multiple audio sources.
Innovation Solution
Leveraging multiple input modalities, such as image and audio signals, to generate content queries by cross-referencing local context and account ecosystem data, enhancing query robustness and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data entry or single modality inputs are used for content retrieval, then the system is simpler to operate, but the measurement precision and reliability of content retrieval decrease
Solution Approach 1:
The patent combines multiple input modalities (audio, visual, contextual signals) into a unified content retrieval system. The computing system receives and processes signals from different modalities simultaneously, merging them to generate comprehensive content queries that improve retrieval precision while managing system complexity through integrated processing architecture.
Solution Approach 2:
The computing system is designed to handle multiple types of input signals (audio from microphones, visual from cameras, contextual from sensors) through a universal processing framework. This multi-functional approach allows the system to accommodate various input modalities without requiring separate specialized processing paths for each type of signal.
2Reliability
If multiple input modalities are used to generate content queries, then the accuracy and robustness of content retrieval improve, but the device complexity and resource usage increase
Solution Approach 1:
The patent segments the content retrieval process into distinct modules: audio signal processing, visual signal processing, contextual signal processing, and query generation. Each modality is processed through dedicated components that independently analyze their specific signal type, then the results are integrated to form the final content query, improving reliability while managing complexity through modular architecture.
Solution Approach 2:
The system introduces an intermediary processing layer that receives raw signals from multiple modalities and transforms them into standardized query representations. This intermediary layer acts as a mediator between the diverse input signals and the content retrieval database, normalizing different modalities into a unified query format that improves reliability without proportionally increasing system complexity.
3Measurement precision
If multiple input modalities are processed to disambiguate audio signals, then the measurement precision in noisy environments improves, but the use of energy and computational resources increase
Solution Approach 1:
The system applies partial processing strategies where not all input modalities are processed with equal intensity for every query. The computing system dynamically determines which modalities to process based on the query context and environmental conditions, applying computational resources selectively to achieve sufficient audio signal discrimination precision without excessive energy consumption when all modalities must be fully processed.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors the quality and relevance of processed signals and adjusts computational resource allocation accordingly. When audio signals are clearly distinguishable, the system reduces processing intensity; when ambiguity detected through visual or contextual signals, the system increases processing resources to enhance discrimination precision, optimizing the balance between measurement precision and energy consumption.
Data Source
AI summary
In an example aspect, the present disclosure provides for an example method for processing queries over content rendering activity. The example method includes receiving, by a computing system comprising one or more processors, a first input signal of a first modality, the first input signal being obtained using one or more sensors of a client device and providing local context signals associated with a content rendering event on an output device. The example method includes receiving, by the computing system, a second input signal of a second modality different from the first modality. The example method includes generating, by the computing system and based on the first input signal and the second input signal, a content query. The example method includes retrieving, by the computing system and based on the content query, a content item associated with the content rendering event.