Virtual Assistant Response Routing in Multi-Participant Conversations
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Solution Overview
Problem
Conventional virtual assistants are limited in their ability to seamlessly integrate into spoken conversations, leading to disjointed or confusing interactions when users attempt to multitask during communication with others.
Innovation Solution
A system that integrates a virtual assistant into a spoken conversation session by processing utterances using machine-trained models to determine intent or content, selectively identifying recipient subsets, and generating responses, allowing for more efficient and effective interaction during real-time communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a virtual assistant is integrated into a spoken conversation session to enable multitasking, then the convenience and usability are improved, but the interaction becomes disjointed, halting, or confusing
Solution Approach 1:
The system segments the conversation participants into different groups based on their relationship to the utterance. The participant who spoke is placed in a 'speaker group,' while other participants are placed in a 'listener group.' This segmentation allows the virtual assistant to selectively provide responses to appropriate groups, maintaining interaction clarity while enabling multitasking.
Solution Approach 2:
The system applies different response rendering qualities to different participant groups. The speaker receives a first response rendered in a first mode (e.g., detailed, immediate), while other participants receive a second response rendered in a second mode (e.g., summarized, delayed). This local quality differentiation resolves the contradiction by tailoring the interaction experience to each participant's role.
2Loss of information
If responses are provided to all participants in a conversation session, then the completeness of information is improved, but the complexity of the system increases
Solution Approach 1:
The system dynamically determines which participants should receive responses based on the utterance content and participant roles. Rather than statically providing responses to all participants or none, the system adaptively selects recipient subsets, reducing information loss while maintaining manageable system complexity through context-aware decision-making.
Solution Approach 2:
The virtual assistant acts as an intermediary that selectively routes information to different participant groups. It mediates between the need for information completeness and system complexity by using intent analysis and participant identification to determine appropriate response distribution, avoiding the need for a simple all-or-nothing approach.
3Speed
If the virtual assistant processes every utterance in real-time during conversations, then the responsiveness is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs partial processing by focusing computational resources only on identifying the speaker and determining the appropriate recipient subset, rather than fully processing and rendering responses for all participants. This selective action maintains responsiveness while reducing overall processing time and resource consumption.
Solution Approach 2:
The system performs preliminary actions by quickly identifying the speaker and determining intent before full response generation. This preliminary processing allows the system to prepare response routing in advance, improving perceived responsiveness while managing computational load through staged processing.
Data Source
AI summary
Techniques for integrating a virtual assistant into a spoken conversation session, the techniques including receiving an utterance information that expresses an utterance spoken by a first participant included in a plurality of participants of a spoken conversation session; processing the utterance information using at least one machine-trained model to determine an intent or content for a command or query included in the utterance; selectively identifying a recipient subset of one or more of the plurality of participants based on at least the determined intent or content for the utterance; generating a response for the command or query; and providing, during the spoken conversation session, the response to the identified recipient subset.