Fuzzy Logic Speech Verification for IVR Systems
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Solution Overview
Problem
Conversational systems, particularly IVR systems, face challenges in accurately identifying and verifying users using speech-based inputs, as existing methods may not effectively handle non-exact matches and require additional authentication factors, which can be inconvenient and less secure.
Innovation Solution
A computer-implemented method utilizing fuzzy logic operations to calculate scores for user data fields from speech inputs, allowing for identification and verification by comparing proposed values with reference values, and using phonetic and orthographic scores to quantify the closeness of matches, thereby supporting non-exact matches and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional exact-match verification methods are used, then security is maintained, but user convenience deteriorates and false negatives increase
Solution Approach 1:
The patent changes the verification parameter from binary exact-match to continuous fuzzy-score matching. By transforming the verification mechanism into a spectrum-based approach using fuzzy logic scores, the system achieves both higher accuracy in handling variations and greater user convenience through fewer reattempts.
2Reliability
If multiple authentication factors are required, then security is improved, but device complexity and operation time increase
Solution Approach 1:
The patent segments the authentication process into multiple user data fields (name, address, date of birth, etc.), each evaluated independently through fuzzy logic. This segmentation allows the system to maintain high security through multi-field verification while avoiding the complexity of traditional multi-factor authentication by using a unified scoring mechanism.
3Productivity
If fuzzy logic scoring is applied, then false negatives are reduced and verification efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies partial fuzzy logic evaluation by processing user data fields in sequence and using early termination when confidence thresholds are met. This partial action approach maintains verification efficiency by avoiding complete computational evaluation when sufficient matches are found, thereby reducing overall computational complexity.
Data Source
AI summary
A computer-implemented method comprising:obtaining, by way of an input, input data relating to speech provided by a user;deriving one or more hypotheses for each of a plurality of user data fields from the input data;obtaining one or more reference values for each of the plurality of user data fields for each of one or more candidate users;calculating a score for at least one candidate user of the one or more candidate users, calculating the score comprising:calculating a plurality of user data field scores comprising, for each of the plurality of user data fields, a respective user data field score using the one or more hypotheses and the one or more reference values for the candidate user for the respective user data field;performing one or more fuzzy logic operations on the plurality of user data field scores;using the score for a candidate user of the one or more candidate users to perform a verification or identification process for the user.