Voice Interface Attribute Weighting for Network Transmission Reduction
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Solution Overview
Problem
Voice-based interfaces face inefficiencies due to users' difficulty in remembering sequential lists of results, leading to excessive network transmissions and resource utilization as users repeatedly request information, causing network traffic congestion and inefficient bandwidth utilization.
Innovation Solution
A system that includes a natural language processor, content selector, and attribute selector to parse audio signals, select relevant attributes for search results based on context, and generate digital components with weighted attributes for efficient data transmission, reducing the need to send all attributes and minimizing network utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If voice-based interfaces sequentially provide all search result attributes to users, then users can access complete information, but users experience difficulty remembering multiple items leading to excessive network transmissions
Solution Approach 1:
The system extracts and transmits only the most relevant attributes for each search result based on context analysis, rather than sending all attributes. This reduces network transmission volume while maintaining essential information quality, directly resolving the contradiction between information completeness and transmission efficiency.
Solution Approach 2:
Different attributes are assigned different levels of importance based on their relevance to the user's search context. The system applies local quality by selectively emphasizing certain attributes over others, ensuring that critical information is preserved while less important data is omitted, thereby reducing overall transmission requirements.
2Loss of information
If the system transmits all attributes for each search result, then users receive comprehensive data, but network bandwidth utilization becomes inefficient due to excessive data volume
Solution Approach 1:
The system extracts only the essential attributes needed for each search result based on contextual relevance. By removing redundant or less important attributes, the system maintains data completeness for critical information while significantly reducing the total data volume transmitted, thus improving bandwidth utilization efficiency.
Solution Approach 2:
Instead of transmitting all possible attributes (excessive action), the system transmits only the necessary subset of attributes (partial action) required for effective user interaction. This partial transmission approach prevents network overload while ensuring sufficient information is provided for user decision-making.
3Adaptability or versatility
If voice-based interfaces provide sequential lists of results, then all search results can be presented, but users struggle to remember each item causing repeated queries
Solution Approach 1:
The system enhances user memory retention by attaching distinctive, context-relevant attributes to each search result. These localized quality markers help users differentiate and remember individual results within the sequential list, reducing the need for repeated queries while maintaining comprehensive search result coverage.
4Loss of information
If the system processes and transmits extensive network traffic data, then complete search information is delivered, but the computing device cannot properly process the data due to capacity limitations
Solution Approach 1:
The system extracts and transmits only the essential attributes required for each search result, reducing the overall data processing burden on computing devices. This extraction approach maintains delivery of critical information while preventing processing capacity overload, directly addressing the contradiction between information completeness and device complexity.
Data Source
AI summary
The present disclosure is generally directed to a data processing system for customizing content in a voice activated computer network environment. The data processing system can provide an improved voice-based interface by selected response attributes based on response weightings. The selection of predetermined attributes can reduce size of response data and reduce network transmissions by providing more succinct audio-based responses.