Speaker Verification Dialogue Generation for Confidence Thresholds
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Solution Overview
Problem
Natural voice interfaces often struggle to accurately recognize speakers, leading to errors and user frustration, especially in environments with low-quality audio or when initial inputs are insufficient for confident speaker verification.
Innovation Solution
An apparatus and method that generate dialogue to solicit additional audio data when the speaker verification score is between lower and higher thresholds, improving confidence by combining initial and additional audio data, and incorporating signal quality measures to adjust interaction flow based on confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speaker verification is performed based on initial audio input only, then the system responds quickly, but the verification accuracy is low leading to errors
Solution Approach 1:
The system dynamically adjusts the verification process based on confidence levels. When the initial verification score falls within an intermediate range (below high confidence threshold but above low confidence threshold), the system transitions from a single-input mode to a multi-turn dialogue mode, adaptively collecting additional audio inputs to improve verification accuracy while managing response time.
Solution Approach 2:
The system performs a preliminary speaker verification using the initial audio input before committing to a final decision. This preliminary action allows the system to assess confidence levels and determine whether additional verification is needed, preventing premature rejections or acceptances based on insufficient data.
2Reliability
If additional dialogue is generated to collect more audio data, then verification confidence improves, but interaction complexity increases
Solution Approach 1:
The system uses confidence level parameters (high confidence threshold, low confidence threshold) to control the verification flow. When the initial verification score falls within the intermediate range, the system generates additional dialogue; otherwise, it proceeds with the initial result. This parameter-based control simplifies the decision logic while improving reliability.
Solution Approach 2:
The system implements a feedback mechanism where the verification score from the initial input determines whether additional dialogue is requested. The additional audio inputs are then used to update the verification score, creating a closed-loop system that iteratively improves confidence while maintaining structured interaction flow.
3Measurement precision
If speaker verification uses strict thresholding, then false acceptances are reduced, but false rejections increase causing user frustration
Solution Approach 1:
The system replaces static thresholding with dynamic confidence assessment. Instead of using a single fixed threshold that causes hard rejections, the system defines a high confidence threshold and a low confidence threshold, creating an intermediate range where additional dialogue is solicited. This dynamic approach reduces false rejections by giving the system opportunity to gather more evidence before making negative decisions.
Solution Approach 2:
The system cushions against potential verification errors by introducing an intermediate confidence range. When verification scores fall within this range, the system proactively solicits additional audio inputs before making a final acceptance or rejection decision, thereby preventing both false acceptances and false rejections that would occur with strict single-threshold approaches.
Data Source
AI summary
An example apparatus for generating dialogue includes an audio receiver to receive audio data including speech. The apparatus also includes a verification score generator to generate a verification score based on the audio data. The apparatus further includes a user detector to detect that the verification score exceeds a lower threshold but does not exceed a higher threshold. The apparatus includes a dialogue generator to generate dialogue to solicit additional audio data to be used to generate an updated verification score in response to detecting that the verification score exceeds a lower threshold but does not exceed a higher threshold.