Multimodal Chatbot Orchestrator for Complex Intent Routing
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Solution Overview
Problem
Current chatbot systems are limited in understanding complex natural language and require manual input, making them inefficient in processing multiple intents within a single statement and failing to simulate natural conversations effectively.
Innovation Solution
A speech analysis system that translates verbal statements into text, detects pauses to divide them into utterances, identifies intents using an orchestrator model, and selects appropriate bots to analyze and respond to each utterance, enabling more conversational and efficient processing of complex statements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single chatbot application is used to process user input, then the system structure is simple, but the chatbot can only understand a limited scope of subject matter and cannot handle complex statements with multiple intents
Solution Approach 1:
The system segments a single complex chatbot into multiple specialized chatbots, each trained on a specific subset of subject matter. An intent classification model divides user input and routes it to the appropriate chatbot(s), enabling the system to handle diverse topics while maintaining specialized expertise in each area.
Solution Approach 2:
The system creates a universal platform that can handle multiple types of subject matter through a combination of intent classification and multiple chatbots. The orchestrator model serves as a universal router that directs different types of queries to appropriate specialized bots, making the overall system versatile across diverse domains.
2Adaptability or versatility
If manual input methods (touchtone digits, menu selection) are required to access chatbots, then the system can route to multiple chatbots, but the natural conversation simulation is reduced
Solution Approach 1:
The system implements self-service by using an automated intent classification model that automatically analyzes user input and routes queries to the appropriate chatbot without requiring manual selection. The model autonomously determines which chatbot(s) should handle the query based on the content and intent of the user's message.
Solution Approach 2:
The system replaces manual mechanical input methods (touchtone digits, menu selection) with an automated natural language processing system. The intent classification model processes user input linguistically and automatically routes queries, substituting the mechanical selection process with an intelligent automated routing mechanism.
3Ease of operation
If a chatbot is designed to understand complex natural language with colloquialisms and slang, then the user experience improves, but the interpretation accuracy decreases due to difficulty in understanding run-on sentences and language adjustments
Solution Approach 1:
The system segments the complex natural language processing task into multiple stages: intent classification, query routing to specialized chatbots, and individual bot processing. This segmentation allows each component to focus on specific aspects of understanding, improving overall accuracy while maintaining natural language处理能力.
Solution Approach 2:
The system applies local quality by training different chatbots on specific subsets of language patterns and subject matter. Each chatbot develops specialized understanding for its domain, allowing for more accurate interpretation of domain-specific colloquialisms and slang while maintaining overall system capability to handle diverse natural language inputs.
Data Source
AI summary
A multi-mode conversational computer system for implementing multiple simultaneous, nearly simultaneous, or semi-simultaneous conversations and/or exchanges of information or receipt of user input includes at least one processor and/or transceiver in communication with at least one memory device; a voice bot configured to accept user voice input and provide voice output; and/or at least one input and output communication channel. The at least one input and output communication channel is configured to communicate with the user via a first channel of the at least one input and output communication channel and the voice bot simultaneously, nearly simultaneously, or nearly at the same time.