Voice Assistant Handoff Using Real-Time Sentiment Analysis
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Solution Overview
Problem
Existing voice-activated assistant systems often struggle with seamless transitions between virtual assistants and live advisors, leading to suboptimal user interactions and satisfaction.
Innovation Solution
A voice-activated user support system that employs a virtual assistant in conjunction with a second assistant, seamlessly transitioning between them based on real-time user interaction and satisfaction parameters, captured through metadata and sentiment analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a voice-activated assistant system uses only a virtual assistant to respond to user queries, then automation extent and productivity are improved, but user satisfaction and interaction quality deteriorate when the virtual assistant cannot adequately handle complex or emotionally charged queries
Solution Approach 1:
The patent introduces a sentiment analysis module as an intermediary between the virtual assistant and the user. This module analyzes user emotions and query complexity in real-time, determining when to transfer the interaction from the automated virtual assistant to a human agent, thus maintaining both automation efficiency and user satisfaction
Solution Approach 2:
The system dynamically adjusts its composition by transitioning between virtual assistant-only mode and hybrid mode (virtual assistant + human agent) based on real-time sentiment analysis results. This dynamic adaptation allows the system to optimize between automation and human intervention depending on user needs
2Reliability
If the system transfers requests to a live advisor frequently to maintain user satisfaction, then user satisfaction parameter is improved, but system latency time and interaction efficiency deteriorate
Solution Approach 1:
The patent changes the threshold parameters for transfer decisions based on sentiment intensity and query type. By adjusting these parameters dynamically, the system optimizes the balance between maintaining user satisfaction and minimizing unnecessary transfers that would increase latency
Solution Approach 2:
The sentiment analysis provides continuous feedback to the system about user satisfaction levels. This feedback loop allows the system to learn from past interactions and refine its transfer decisions, reducing unnecessary transfers while maintaining high user satisfaction
3Ease of operation
If the system implements comprehensive sentiment analysis and multiple parameter monitoring to ensure seamless transitions, then user interaction quality is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent segments the sentiment analysis into distinct modules: emotion detection, query complexity analysis, and transfer decision-making. This segmentation allows each module to specialize in specific tasks, improving overall accuracy while managing computational complexity through modular design
Solution Approach 2:
The virtual assistant system is designed with multi-functionality, serving both as the primary response mechanism and as the interface for sentiment analysis. This universal design reduces overall system complexity by eliminating the need for separate dedicated analysis systems
Data Source
AI summary
The concepts include a user support system in the form of a microphone, a visual display arranged in a vehicle cabin, and a controller. The controller includes an instruction set that is executable to receive, via the microphone, a voice-based request from a user, and employ a virtual assistant to determine a user interaction in real time and to determine a specific intent for the voice-based request, including capturing metadata. A user interaction routine determines a user interaction parameter associated with the virtual assistant based upon the voice-based request from the user. A user sentiment analysis routine determines a user satisfaction parameter associated with the virtual assistant based upon the voice-based request from the user. The controller responds in real-time to the voice-based request based upon the user satisfaction parameter and the user interaction parameter that are associated with the virtual assistant.