Script Compliance Detection Using Key Term Distance Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for verifying script compliance in audio interactions are labor-intensive and prone to errors due to background noise and detection issues, making it impractical for large volumes of interactions.
Innovation Solution
A computer-implemented method that extracts key terms from a script, generates a query based on these terms, and determines the relevance score of audio interactions by considering constraints such as order and distance between key terms, using recognizability and uniqueness scores to filter and sort interactions for compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual listening to audio conversations is used for script compliance determination, then detection accuracy can be maintained, but labor intensity increases significantly and productivity decreases
Solution Approach 1:
The patent replaces the mechanical manual listening process with an automated computer-based audio analysis system. The system uses speech-to-text conversion, natural language processing, and automated script matching algorithms to detect compliance without human intervention, thereby eliminating labor intensity while maintaining detection accuracy through systematic computational analysis.
Solution Approach 2:
The patent introduces an intermediary automated processing layer between the audio conversation and the compliance determination. This intermediary system performs speech recognition, text analysis, and script comparison functions, acting as a mediator that translates audio signals into compliance assessments without requiring direct human listening, thus resolving the contradiction between accuracy and productivity.
2Reliability
If searching for the full script in audio signal is performed, then complete script verification is achieved, but detection reliability fails due to detection errors, background noises, and agent errors
Solution Approach 1:
The patent divides the full script into multiple key terms or phrases that are searched for separately in the audio conversation. Instead of requiring exact full-script matching, the system identifies and locates these segmented key terms, which makes the detection more robust to background noise and minor speech variations while maintaining verification completeness through the collective identification of all segments.
Solution Approach 2:
The patent employs partial matching by searching for key terms rather than requiring complete script verification. This partial action approach allows the system to identify compliance even when the full script is not perfectly reproduced, accommodating detection errors and agent variations while still achieving reliable compliance determination through the presence of critical key terms.
3Ease of operation
If only one or a few predetermined words are detected in audio signal, then detection simplicity is maintained, but script verification completeness is insufficient as detected words may not constitute a full script
Solution Approach 1:
The patent creates a multi-functional detection system that can identify multiple key terms within a single audio analysis pass. The system is designed to search for and detect several predetermined words or phrases simultaneously, making the detection process simple yet comprehensive. This universal approach allows the same detection mechanism to handle various script requirements by simply changing the set of key terms being searched, thereby maintaining both simplicity and verification accuracy.
Data Source
AI summary
A method, computerized apparatus and computer program product for determining script compliance in interactions, the method comprising: receiving one or more indexed audio interaction; receiving a text representing a script; automatically extracting two or more key terms from the script; automatically generating a query representing the script, comprising: receiving one or more constraint associated with the at least two key terms; and determining spotted key terms of the key terms that appear in the indexed audio interactions; determining complied constraints based on a number of words difference between two key terms of the at least two key terms; and determining a relevance score for each of the indexed audio interactions, based on the spotted key terms and the complied constraints.