Robot Conversational Context Recognition for Natural Response Timing
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Solution Overview
Problem
Robots in Human Robot Interaction (HRI) contexts often generate responses at inappropriate timings, leading to unnatural interactions due to inadequate identification of social interaction context information.
Innovation Solution
An apparatus and method for recognizing conversational context in robots using multimodal recognition of audio and video from a robot's Point-of-View (POV) video to classify social interaction states and generate appropriate responses based on the identified speaker and intended recipient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the robot actively intervenes in conversations, then the robot can provide assistance and show engagement, but the interaction becomes unnatural when the intervention timing is inappropriate
Solution Approach 1:
The robot performs preliminary analysis of the conversation context, speaker identity, and intended recipient before deciding to intervene. This advance preparation allows the robot to timing its interventions appropriately, ensuring they occur only when relevant to the ongoing conversation rather than randomly or inappropriately.
Solution Approach 2:
The robot continuously monitors the conversation context, speaker gestures, and interpersonal dynamics in real-time, using this feedback to dynamically adjust its intervention timing. By analyzing the flow of conversation and detecting appropriate moments, the robot can intervene naturally when needed and remain quiet when the conversation is flowing smoothly between users.
2Productivity
If the robot responds to all audio inputs, then the robot can maintain constant engagement, but the robot intervenes even when not called or when users are conversing without intending to involve the robot
Solution Approach 1:
The robot extracts and analyzes specific features from audio inputs, including speaker identification, gaze direction, and conversational context, rather than responding to all audio equally. By selectively processing only relevant audio cues and filtering out unnecessary inputs, the robot can maintain appropriate engagement levels without over-intervening in conversations that don't require its participation.
Solution Approach 2:
The robot dynamically adjusts its response threshold and sensitivity based on the detected social context, speaker intentions, and conversation flow. When users are engaged in a private conversation, the robot raises its intervention threshold; when the context indicates a need for assistance or acknowledgment, the robot lowers the threshold and responds appropriately. This parameter adjustment allows flexible control over response frequency and appropriateness.
Data Source
AI summary
Disclosed herein are an apparatus and method for recognizing a conversational context in a robot. The apparatus for recognizing a conversational context in a robot includes memory configured to store at least one program, and a processor configured to execute the program, wherein the program is configured to perform recognizing a speaker and an intended recipient from a robot's Point-of-View (POV) video, and classifying a social interaction state of the robot as one of predefined social interaction states depending on the recognized speaker and the recognized intended recipient.