Vehicle Agent System Active Conversation Topic Selection
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Solution Overview
Problem
Existing vehicle agent systems lack the ability to actively determine dialogue topics and identify listeners, resulting in passive interactions with occupants.
Innovation Solution
An agent system comprising a microphone, speaker, interpretation unit, memory, and control processor that collects and interprets occupant voices, designates frequent utterers as listeners, and outputs relevant topics via the speaker, using AI and portable device data to facilitate active conversations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system only responds to occupant inputs passively, then the system complexity is reduced, but the conversational engagement and user satisfaction deteriorate
Solution Approach 1:
The system performs preliminary analysis of occupant utterances during the conversation, accumulating data on who speaks most frequently. This preliminary action enables the system to proactively determine the listener and select appropriate topics without requiring complex real-time decision-making, thus improving conversational engagement while managing system complexity
Solution Approach 2:
The system serves itself by automatically analyzing conversation patterns, identifying the frequent speaker as the listener, and selecting topics independently. This self-service mechanism reduces the need for external control complexity while maintaining active conversational engagement
2Productivity
If the system actively determines topics and identifies listeners, then the conversational quality improves, but the processing time and computational resources increase
Solution Approach 1:
The system accumulates utterance data during the conversation in advance, preparing the foundation for listener identification and topic selection before they are needed. This preliminary data accumulation reduces the processing time required when the system needs to actively determine topics and listeners
Solution Approach 2:
The system focuses on a specific, partial action of analyzing only the frequency of occupant utterances to identify the listener, rather than performing comprehensive analysis of all conversation aspects. This partial action approach maintains high conversational quality while reducing computational overhead and processing time
Data Source
AI summary
An agent system includes a microphone, a speaker, an interpretation unit, a memory, and a control processor. The microphone collects voices of occupants in the interior of a vehicle compartment of a vehicle. The speaker outputs a voice sound to the interior of the vehicle compartment. The interpretation unit acquires the voices of the occupants collected by the microphone and interprets contents of utterances of the occupants included in the voices acquired. The memory stores data on the utterances interpreted by the interpretation unit and data on the respective occupants who are utterers of the utterances associated with each other. The control processor designates an occupant who has uttered most frequently among the occupants as a listener based on the data stored in the memory, determines topics to be outputted to the listener, and performs control to output the topics as the voice sound via the speaker.