Empathy degree prediction system, emmpathy degree prediction method, and program

The empathy prediction system enhances accuracy by combining semantic and visual cues from speech and video data to predict empathy levels, addressing the limitations of existing methods in evaluating diverse conversational information.

WO2026116374A1PCT designated stage Publication Date: 2026-06-04HONDA MOTOR CO LTD
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Patent Information

Application Number
PCT/JP2025/041200
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-11-27
Filing Date
2025-11-26
Publication Date
2026-06-04

AI Technical Summary

Technical Problem

Existing methods for predicting empathy levels in conversations are not accurate due to the lack of comprehensive evaluation of diverse information types, such as speech content, facial expressions, and actions, which limits the precision of empathy assessment.

Method used

An empathy prediction system that combines text and video information by extracting semantic and visual cues, using a coupling unit to generate combined information, and employing a pattern-based classifier to predict empathy levels accurately.

Benefits of technology

Improves the accuracy of empathy level prediction by integrating semantic cues from speech and visual cues, such as facial expressions and head posture, enhancing the precision of empathy assessment in human-robot interactions.

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Abstract

This empathy degree prediction system comprises: a text information acquisition unit for acquiring text information based on voice of a subject; a video information acquisition unit for acquiring video information of the subject; a semantic clue extraction unit for extracting a semantic clue from the text information; a visual clue extraction unit for extracting a visual clue from the video information; a connection unit for connecting the semantic clue and the visual clue to generate connection information; and an empathy degree prediction unit for predicting an empathy degree of the subject on the basis of the connection information.
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Citation Information

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