Domain-Specific Voice Model Generation for Networked Systems
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Solution Overview
Problem
In networked environments, users face inefficiencies when seeking additional information related to content, as they often need to leave the current resource to access it, leading to increased network bandwidth usage and follow-up input requests for unclear voice-based queries.
Innovation Solution
A system that generates domain-specific natural language processing models, utilizing a data processing system with a natural language processor and digital component selector to parse voice inputs, select relevant digital components, and transmit responses within the existing interface, reducing the need for follow-up requests and bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users leave the currently viewed resource to access additional information, then information completeness is improved, but network bandwidth usage increases and user convenience deteriorates
Solution Approach 1:
The patent introduces a digital component as an intermediary element that embeds additional information directly within the currently viewed resource. This digital component acts as a mediator between the user and the additional information, allowing users to access supplementary content without navigating away from the main resource, thus maintaining user convenience while improving information completeness
Solution Approach 2:
The patent implements nesting by embedding a digital component (containing additional information) within the existing resource structure. The digital component is nested inside the currently viewed resource, allowing users to access layered information without leaving the parent resource, thereby resolving the contradiction between information completeness and user convenience
2Loss of information
If users leave the currently viewed resource to access additional information, then information completeness is improved, but network bandwidth usage increases
Solution Approach 1:
The digital component serves as an intermediary that delivers additional information locally within the current resource context, eliminating the need for users to navigate to separate resources. This reduces network bandwidth usage by avoiding additional page loads or resource requests, while still providing complete information through the embedded digital component
Solution Approach 2:
The patent applies preliminary action by pre-embedding the digital component with additional information into the resource before the user accesses it. This preparation allows the information to be immediately available within the current resource view, eliminating the need for subsequent network requests and reducing overall bandwidth consumption
3Productivity
If the system provides specific responses to unclear voice-based queries, then user interaction efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the digital component to automatically respond to user interactions with unclear voice-based queries. The system uses the knowledge graph to autonomously determine appropriate responses without requiring complex manual intervention, thereby improving user interaction efficiency while managing system complexity through automated decision-making
Solution Approach 2:
The patent applies feedback by creating a closed-loop system where the digital component receives user queries, processes them through the knowledge graph, and provides responses that feed back into the interaction. This feedback mechanism allows the system to learn from and adapt to user interactions, improving efficiency over time while the underlying complexity remains managed through structured processing
Data Source
AI summary
The present disclosure is generally directed to the generation of domain-specific, voice-activated systems in interconnected networks. The system can receive input signals that are detected at a client device. The input signals can be voice-based input signals, text-based input signals, image-based input signals, or other type of input signals. Based on the input signals, the system can select domain-specific knowledge graphs and generate responses based on the selected knowledge graph.