Virtual Assistant Out-of-Scope Inquiry Handling
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Solution Overview
Problem
Conventional virtual assistants operate on a linear and isolated task-based approach, leading to sub-optimal results due to single interpretation of user intent, lack of collaboration between tasks, and inability to handle multi-turn interactions or exclusionary commands, resulting in limited contextual understanding and accuracy.
Innovation Solution
A method and system that generate multiple primary and secondary interpretations of user input, allowing for parallel processing and collaboration between tasks, with scoring based on conversational state, user profile, and auxiliary metadata to provide accurate and context-aware responses, and the ability to handle out-of-scope or out-of-domain inquiries by utilizing anomaly detection and textual comprehension modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a single interpretation path is used for processing user input, then the processing speed is fast, but the accuracy of understanding user intent deteriorates
Solution Approach 1:
The patent segments the user input processing into multiple parallel interpretation paths, where each path generates a possible transcription and corresponding user intent. Instead of relying on a single linear path, the system creates multiple hypotheses simultaneously, allowing for more accurate intent recognition while maintaining efficient processing through parallel execution.
Solution Approach 2:
The patent adds a dimensional expansion to the processing architecture by introducing multiple interpretation layers (primary transcriptions, secondary transcriptions, and alternative interpretations). This multi-dimensional approach allows the system to explore various possible meanings of user input concurrently, improving accuracy without sacrificing speed through the use of parallel processing dimensions.
2Measurement precision
If multiple interpretations are generated and processed in parallel, then the accuracy of user intent understanding is improved, but the system complexity increases
Solution Approach 1:
The patent divides the complex interpretation task into manageable segments: primary transcription generation, secondary transcription generation, alternative interpretation creation, and scoring. Each segment handles a specific aspect of the interpretation process, making the overall complex system more manageable and maintainable while still achieving high accuracy through the coordinated work of these segmented components.
Solution Approach 2:
The system implements self-service mechanisms through automated scoring and selection processes. The multiple interpretations are automatically evaluated against conversational state, user profile, and auxiliary metadata, with the highest-scoring interpretation selected without requiring manual intervention. This self-service approach reduces operational complexity while maintaining high interpretation accuracy.
3Productivity
If only the top textual representation is selected for processing, then the processing efficiency is high, but the contextual understanding deteriorates
Solution Approach 1:
The patent performs preliminary actions by generating multiple primary and secondary transcriptions and alternative interpretations before the actual intent determination. This preliminary expansion ensures that contextual information is preserved across multiple hypotheses, and the most contextually appropriate interpretation can be selected based on scoring against conversational state and user profile, rather than losing context by selecting only the top transcription.
Solution Approach 2:
The system uses feedback mechanisms where interpretations are scored based on conversational state, user profile, and auxiliary metadata. This feedback loop allows the system to evaluate multiple interpretations against known context and select the one that best preserves contextual understanding, rather than blindly following the top textual representation without contextual validation.
4Ease of manufacture
If a linear task-based approach is used, then the system is simple to implement, but the ability to handle multi-turn interactions and exclusionary commands deteriorates
Solution Approach 1:
The patent introduces dynamics into the system by allowing the interpretation and processing path to adapt based on conversational state and user profile. The system can dynamically adjust which interpretations to pursue and how to handle exclusionary commands like 'but not' by back-tracing through previous interpretations. This dynamic adaptability enables multi-turn interactions while maintaining a relatively simple underlying architecture through the use of standardized processing components.
Data Source
AI summary
Disclosed is a system and method for processing out of scope or out of domain user inquiries with a first virtual assistant, which may include the steps of receiving a user request at a user device and converting the user request into a user inquiry, interpreting the user inquiry with an anomaly detection system to generate an interpretation of the user inquiry, forming a question from the interpretation using a textual composition module, accessing a dataset of text-based descriptions of a scope of the first virtual assistant using a textual composition module and a scope of an external source using a textual composition module, querying the dataset for an answer to the question, and when the answer is found in the description of the scope of an external source, transmitting the user inquiry to the external source for processing to generate a response to the user inquiry.