Interactive Communication System Dissatisfaction Detection
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Solution Overview
Problem
Conventional interactive communication systems often fail to detect user dissatisfaction in real-time, leading to poor user experiences and increased likelihood of call termination, as they struggle to accurately recognize input and handle complex tasks efficiently.
Innovation Solution
An interactive communication system uses a cumulative predictor model to analyze dialog chunks, generating feature sets and scores to determine the likelihood of user dissatisfaction, triggering remedial actions such as transferring calls to human operators or altering dialog plans when the dissatisfaction threshold is exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional interactive communication systems use basic dialog processing, then system complexity is low, but user dissatisfaction detection accuracy is poor
Solution Approach 1:
The patent segments the dialog into multiple chunks and extracts features from each chunk separately. The cumulative predictor model processes these segmented features to determine dissatisfaction likelihood, allowing accurate detection without requiring the entire dialog to be analyzed at once, thus managing system complexity while improving detection accuracy.
Solution Approach 2:
The system performs preliminary actions by pre-defining feature extraction rules and cumulative predictor models before actual dialog analysis. This preparation enables the system to quickly assess dissatisfaction likelihood during the call without complex real-time processing, resolving the contradiction between accuracy and complexity.
2Reliability
If the system monitors user dissatisfaction in real-time, then user experience improves, but processing time and computational resources increase
Solution Approach 1:
By segmenting the dialog into chunks and processing features from each chunk incrementally, the system provides real-time dissatisfaction monitoring without requiring to wait until the end of the entire dialog. This segmentation enables timely intervention while managing processing time efficiently.
Solution Approach 2:
The system implements feedback by continuously monitoring dissatisfaction likelihood and triggering remedial actions when thresholds are exceeded. This real-time feedback loop improves user experience by addressing issues promptly while using efficient processing to minimize time loss.
3Measurement precision
If the system uses detailed feature extraction from dialog chunks, then dissatisfaction detection accuracy improves, but computational complexity increases
Solution Approach 1:
The patent extracts features from segmented dialog chunks rather than analyzing the entire dialog at once. This segmentation allows detailed feature extraction to improve accuracy while managing computational complexity by processing smaller, manageable portions of the dialog incrementally.
Data Source
AI summary
An interactive communication system configured to conduct a call with a caller. The interactive communication system comprises at least one computer hardware processor configured to perform: obtaining a plurality of dialog chunks comprising information provided by the caller to the interactive communication system and information provided by the interactive communication system to the caller; generating, based on the plurality of dialog chunks, a respective plurality of feature sets, each of the plurality of feature sets comprising at least one feature generated using a respective dialog chunk of the plurality of dialog chunks; determining, based on the plurality of feature sets, a respective plurality of dialog chunk scores; determining, based at least in part on the plurality of dialog chunk scores, a likelihood that the caller is dissatisfied with the interactive communication system; and when the likelihood exceeds a threshold, performing a remedial action that alters how the call is handled.