Speech Recognition Diagnostic Tool for IVR Failure Analysis
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Solution Overview
Problem
Conventional speech recognition systems lack effective diagnostic tools to identify and analyze failure points in IVR applications, leading to high opt-out rates due to recognition errors, unclear instructions, and cumbersome application flows, making it difficult to optimize and maintain cost savings from automated call processing.
Innovation Solution
A diagnostic tool that records and compares multiple speech recognition sessions to identify common failure points, allowing administrators to review and adjust the application flow to reduce opt-out rates by analyzing and tuning the system to recognize specific utterances and improve user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If speech recognition systems are deployed in IVR applications to automate call processing, then operational costs are reduced and productivity increases, but recognition errors and application failures occur leading to high opt-out rates
Solution Approach 1:
The system records multiple speech sessions and provides feedback mechanisms including session playback, failure point identification, and confidence level analysis. Administrators can review recorded sessions, identify recognition errors, and use this feedback to continuously improve the speech recognition application, thereby reducing opt-out rates while maintaining automation benefits
Solution Approach 2:
The patent introduces an intermediary diagnostic tool that sits between the speech recognition system and the administrator. This tool captures speech sessions, analyzes confidence levels, identifies failure points, and presents structured information to administrators, enabling them to effectively tune and optimize the recognition system without requiring deep technical expertise
2Measurement precision
If administrators manually review individual speech sessions to identify failure points, then recognition accuracy can be improved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically recording multiple speech sessions and pre-processing them to identify failure points and confidence levels before administrator review. Sessions are captured and annotated with metadata including recognition confidence, failure points, and session outcomes, so administrators only need to review pre-analyzed data rather than raw audio
Solution Approach 2:
The patent segments the diagnostic process into distinct components: session recording, confidence level analysis, failure point identification, and structured presentation. Each speech session is broken down into discrete utterances with associated confidence scores, allowing administrators to efficiently navigate and analyze specific failure points without reviewing entire sessions
3Reliability
If the speech recognition system uses strict confidence thresholds to ensure accuracy, then recognition reliability improves, but more callers opt-out due to rejected utterances
Solution Approach 1:
The system dynamically adjusts confidence thresholds based on contextual factors and caller behavior patterns. Rather than applying a static threshold to all utterances, the system can lower thresholds for certain contexts or callers who have demonstrated tolerance for uncertainty, thereby maintaining recognition reliability while reducing unnecessary opt-outs
Data Source
AI summary
A diagnostic tool for speech recognition applications is provided, which enables a administrator to collect multiple recorded speech sessions. The administrator can then search for various failure points common to one or more of the recorded sessions in order to get a list of all sessions that have the same failure points. The invention allows the administrator to playback the session or replay any portion of the session to see the flow of the application and the recorded utterances. The invention provides the administrator with information about how to maximize the efficiency of the application which enables the administrator to edit the application to avoid future failure points.