Multi-Intent Response Generation with Specialized Topic Routing
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Solution Overview
Problem
Conversational software algorithms struggle to accurately process multi-intent and multi-topic user inputs, often ignoring or underweighting latter words, failing to understand compact sentences, and not addressing all requests due to training on single-intent inputs, leading to incomplete or invalid responses.
Innovation Solution
The system splits multi-intent inputs into logical portions, each associated with a single topic or request, and processes each portion through specialized conversational software algorithms to generate accurate responses, reordering operations if necessary and correcting invalid responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single conversational software algorithm is used to process multi-intent input, then the system structure remains simple, but the accuracy and completeness of response deteriorates as input complexity increases
Solution Approach 1:
The patent divides the complex multi-intent input processing into multiple specialized conversational software algorithms, each trained to handle specific intents or topics. This segmentation allows each algorithm to focus on a narrower scope, improving accuracy while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The system creates a universal processing framework that can handle diverse multi-intent inputs by coordinating multiple specialized algorithms. Each algorithm maintains its specialized function while the overall system achieves multi-functionality by routing different input portions to appropriate algorithms based on detected intents.
2Loss of information
If the input length increases with multiple requests, then more information can be conveyed, but the latter words are ignored or given less weight leading to incomplete processing
Solution Approach 1:
The system segments long multi-intent inputs into smaller portions, each associated with specific intents or topics. By dividing the input processing into manageable chunks handled by specialized algorithms, the system prevents information loss in latter portions while maintaining efficient processing through parallel or sequential handling of segments.
Solution Approach 2:
The system performs preliminary analysis to identify and separate different intents within the input before processing. This preliminary segmentation ensures that all parts of the input, including latter words, are properly recognized and routed to appropriate algorithms, preventing information loss while optimizing processing efficiency.
3Measurement precision
If the system processes each split portion through separate algorithms, then response accuracy improves, but the device complexity increases
Solution Approach 1:
The patent implements a universal orchestrator that manages multiple specialized algorithms, enabling the system to achieve high response accuracy through coordinated processing while maintaining manageable complexity through a standardized interface and routing mechanism that works across all algorithm interactions.
4Ease of manufacture
If current conversational agents are trained on single-intent inputs, then training data requirements are reduced, but the ability to understand compact sentences with multiple intents deteriorates
Solution Approach 1:
The system segments multi-intent training data into separate intent portions, each processed by specialized algorithms trained on specific intent types. This approach maintains training ease by keeping each algorithm's training focused and manageable while achieving superior multi-intent understanding through the coordinated output of multiple specialized models.
Data Source
AI summary
A system receives an input from a user, where the input indicates a request to perform one or more tasks. The system generates a plurality of utterances from the input. Each utterance indicates a different operation. The system determines a sequence of the operations to be performed in order to perform the one or more tasks. The system identifies a conversational software algorithm that is configured to process a respective utterance based on the topic of the utterance. The system communicates each utterance to the respective conversational software algorithm. The system receives responses from the conversational software algorithms. The system determines whether each response is valid. The system generates a final response based on the valid responses. The system outputs the final response.