Meeting Voice Processor for Psychological State Estimation
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Solution Overview
Problem
Existing meeting support systems fail to effectively evaluate the psychological state of meeting participants based on the purpose of the meeting, leading to deviations in determining psychological safety and barriers during discussions.
Innovation Solution
An information processing device and program that utilize a voice processor to extract feature amounts from speech, an estimator to assess the likelihood of a psychological state, and a determiner to evaluate psychological safety based on predetermined index values specific to the meeting purpose, incorporating weighting for accurate psychological state determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing meeting support systems evaluate speech content without considering psychological state, then speech evaluation can be conducted, but the evaluation deviates from the meeting purpose and fails to accurately determine psychological safety
Solution Approach 1:
The system segments the evaluation process into distinct functional modules: a voice processor that extracts acoustic features, an estimator that calculates psychological state likelihoods, and a determiner that integrates these with meeting purpose index values. This segmentation allows each component to specialize in specific tasks, improving overall measurement precision while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary estimation process between raw voice data and final psychological safety determination. The estimator acts as a mediator that transforms voice features into psychological state likelihoods, which are then combined with meeting purpose index values by the determiner. This intermediary layer enables accurate psychological state assessment without directly complicating the overall system architecture.
2Adaptability or versatility
If the system uses generic speech evaluation methods, then implementation is simple, but it cannot accurately determine psychological safety aligned with meeting purpose
Solution Approach 1:
The system applies local quality by incorporating meeting-purpose-specific index values that tailor the evaluation criteria to each meeting's objectives. The determiner unit uses these localized index values (e.g., different weights for brainstorming vs. decision-making meetings) to adapt the psychological state assessment to the specific context, thereby improving both adaptability and measurement precision simultaneously.
Solution Approach 2:
The evaluation system is designed to be dynamic by allowing index values to be adjusted according to different meeting purposes and conditions. The determiner can adaptively weight various psychological state indicators based on the specific meeting context, enabling the system to maintain high measurement precision across diverse meeting types while remaining versatile.
3Measurement precision
If the system does not incorporate voice feature extraction and psychological state estimation, then the system remains simple, but it cannot quantitatively determine psychological safety likelihood
Solution Approach 1:
The patent replaces subjective psychological assessment with an automated processing system that uses voice feature extraction and statistical estimation. The voice processor extracts acoustic features objectively, the estimator applies mathematical models to calculate likelihoods, and the determiner integrates these with index values. This substitution of mechanical/algorithmic processes for subjective judgment enables quantitative determination of psychological safety while managing complexity through automation.
Data Source
AI summary
An information processing device that determines a psychological state of a member in a meeting, includes: a voice processor that extracts a predetermined feature amount from a voice of a part corresponding to a speech of the member among voices collected during the meeting by a microphone; an estimator that receives an input of a feature amount and estimates a likelihood that the member is in a predetermined psychological state; and a determiner that determines a likelihood that the member is in the predetermined psychological state during the meeting on a basis of the likelihood estimated by the estimator and an index value according to a purpose of the meeting.