Virtual Assistant Emotional Context Analysis
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Solution Overview
Problem
Current virtual assistants lack the ability to consider emotional and contextual factors in social service contexts, leading to limited and ineffective responses in person-to-person interactions.
Innovation Solution
A system and method that utilize a computing device to receive personal and contextual information about participants during activity sessions, access a database of previous sessions, and generate intelligent recommendations based on emotional assessments and scenario types to improve interaction outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If virtual assistants operate using programmed rules, then the scope of queries that may be addressed is determined, but the depth of the response is limited and fails to address emotional or special context
Solution Approach 1:
The system pre-processes and stores emotional context data from audio recordings during activity sessions, creating a knowledge base of emotional patterns and outcomes before they are needed for decision-making. This preliminary action enables the virtual assistant to access relevant emotional context quickly during interactions without compromising response time
Solution Approach 2:
The patent introduces an emotional context analysis module as an intermediary between the audio input and the virtual assistant's response generation. This intermediary processes audio recordings to extract emotional states and contextual factors, then feeds this enriched information to the response system, enabling deeper contextual understanding while maintaining the structured operation of the virtual assistant
2Productivity
If virtual assistants provide automated responses, then efficiency is improved, but the human factor and emotional context are not appreciated
Solution Approach 1:
The system implements feedback loops where outcomes of activity sessions are recorded and analyzed to improve future emotional context recognition. The virtual assistant learns from past interactions by analyzing which emotional assessments correlated with successful outcomes, continuously refining its emotional understanding while maintaining automated efficiency
Solution Approach 2:
Audio recordings are pre-analyzed to extract emotional context and store this information in advance of when it might be needed for response generation. This preliminary processing of emotional data allows the system to maintain high response efficiency while incorporating rich emotional context that would otherwise be lost in automated processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides effective guidance to facilitators by identifying approaches that have led to positive outcomes in similar scenarios, enhancing the likelihood of successful interactions and participant engagement.
Implementation Method 1
detecting a speech signal in the audio recording corresponding to the one or more utterances
Implementation Method 2
recognizing a first emotional state in a first segment of the speech signal based on an analysis of its acoustic characteristics
Data Source
AI summary
A system and method for improving outcomes in various person-to-person goal-oriented interactions is disclosed. Specifically, the method and system enable intelligent insights and recommendations to be presented to a facilitator of the interaction via a virtual assistant user interface. When the facilitator seeks to produce a specific goal with respect to the participant, the system can be configured to automatically generate, based on a series of inputs about the participant and previous interactions, intelligent recommendations that have a high likelihood of successfully promoting the target goal in the current scenario.