Generic Virtual Assistant Platform Segmentation
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Solution Overview
Problem
Existing dialog-driven interactive applications require significant investment and specialized knowledge to design and maintain, as they need to be customized for each domain, leading to inefficiencies in development and deployment.
Innovation Solution
A generic virtual personal assistant platform is introduced, which separates domain-independent core logic from domain-specific plug-ins, allowing for rapid configuration and deployment across various domains without the need for extensive programming, using a generic language understanding module and task reasoning module with domain-specific models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional dialog-driven interactive applications are designed and built with significant investment of time and money, then the system can be customized for each domain, but the development cost and time increase significantly
Solution Approach 1:
The system is divided into domain-independent core components (language understanding module, task reasoning module) and domain-specific plug-ins. This segmentation allows the core logic to be reused across domains while only the plug-ins need to be customized, dramatically reducing development time and cost.
Solution Approach 2:
The generic virtual personal assistant platform is designed to serve multiple domains through a single universal core system. The language understanding module and task reasoning module can handle various domains by loading different plug-ins, eliminating the need to build separate systems for each domain.
2Reliability
If traditional interactive voice response systems are designed with specialized knowledge requirements, then the system can handle complex domain-specific tasks, but the barrier to entry and maintenance difficulty increase
Solution Approach 1:
Business experts can define domain-specific behaviors and workflows using intuitive interfaces without requiring programming expertise. The system automatically translates these definitions into executable task flows, allowing non-technical users to customize domain-specific functionality.
Solution Approach 2:
The platform provides an intermediary layer between business experts and the core system. Domain-specific models and task flows act as translators that convert business logic into system-executable instructions, eliminating the need for direct programming expertise.
3Adaptability or versatility
If domain-specific virtual assistants are built from scratch for each domain, then the system can be optimized for that domain, but the development cost and complexity increase
Solution Approach 1:
The system separates domain-independent core components from domain-specific plug-ins. This segmentation reduces overall system complexity by allowing the core to remain simple and reusable, while only the plug-ins need to be customized for each domain.
Solution Approach 2:
Instead of building each domain-specific assistant from scratch, the system uses templates and plug-ins that can be copied and configured for different domains. This reduces complexity by reusing proven architectural patterns across domains.
Data Source
AI summary
A method for assisting a user with one or more desired tasks is disclosed. For example, an executable, generic language understanding module and an executable, generic task reasoning module are provided for execution in the computer processing system. A set of run-time specifications is provided to the generic language understanding module and the generic task reasoning module, comprising one or more models specific to a domain. A language input is then received from a user, an intention of the user is determined with respect to one or more desired tasks, and the user is assisted with the one or more desired tasks, in accordance with the intention of the user.